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Mohammad Zarbi, Reza Safdari, Nahid Einollahi,
Volume 14, Issue 6 (1-2021)
Volume 14, Issue 6 (1-2021)
Abstract
Background and Aim: Medical diagnostic laboratories are among the most important centers in the treatment cycle of patients. Today, the conscious choice of such laboratories is one of the challenges that patients face in the treatment process. This study was conducted with the aim of improving the knowledge of software users in the field of laboratory sciences and also facilitating the conscious and intelligent selection of the laboratory required by users.
Materials and Methods: This is a descriptive-developmental research with an applied approach. The steps consisted of library studies, questionnaire-based needs assessment, collection of knowledge and identity data, design through drawing UML diagrams, implementation using Java programming language, and software evaluation.
Results: A comprehensive system of laboratory information and experiments can be performed in all laboratories in Tehran, based on factors such as location access, types of laboratories and types of tests, a system was designed that allows users to access the most appropriate laboratory centers with high speed and less mobility, sufficient information, and in accordance with their needs. The evaluation was done using a researcher-made questionnaire whose validity and reliability were confirmed. The target population consisted of eleven specialists and forty ordinary users. According to the Likert criterion, the results obtained from the answers of all participants in the study to the questions of the questionnaire were higher than 4.05.
Conclusion: The software showed that the factors that had priority in the need assessment significantly increased user satisfaction and also provided ease of use of laboratory services in accordance with users' needs.
Materials and Methods: This is a descriptive-developmental research with an applied approach. The steps consisted of library studies, questionnaire-based needs assessment, collection of knowledge and identity data, design through drawing UML diagrams, implementation using Java programming language, and software evaluation.
Results: A comprehensive system of laboratory information and experiments can be performed in all laboratories in Tehran, based on factors such as location access, types of laboratories and types of tests, a system was designed that allows users to access the most appropriate laboratory centers with high speed and less mobility, sufficient information, and in accordance with their needs. The evaluation was done using a researcher-made questionnaire whose validity and reliability were confirmed. The target population consisted of eleven specialists and forty ordinary users. According to the Likert criterion, the results obtained from the answers of all participants in the study to the questions of the questionnaire were higher than 4.05.
Conclusion: The software showed that the factors that had priority in the need assessment significantly increased user satisfaction and also provided ease of use of laboratory services in accordance with users' needs.
Niloofar Mohammadzadeh, Ziba Mosayebi, Hamid Beigy, Mohammad Shojaeinia,
Volume 14, Issue 6 (1-2021)
Volume 14, Issue 6 (1-2021)
Abstract
Background and Aim: Sepsis is the most important disease in the first 28 days of life and one of the main causes of infant mortality in the intensive care unit. Its definitive diagnosis is possible by performing blood culture. Neonatal sepsis can be a clinical sign of nosocomial infections that are often resistant to antibiotics. Therefore, the purpose of this study was to create and evaluate a hospital sepsis prediction model and present its results to health care providers.
Materials and Methods: In this descriptive-applied study, the research population includes neonates admitted to the intensive care unit of Valiasr Hospital in Tehran and the research sample is the data of 4196 neonates admitted to this ward from 2016 to August, 2020. The initial features for creating a predictive model of sepsis were prepared by examining the relevant information sources and under the supervision of professors and officials of Valiasr Hospital's mother and fetus research center and its validity was confirmed by 5 neonatal professors of this hospital. In this research, machine learning algorithms have been used to create a sepsis prediction model.
Results: Accuracy and AUROC(area under the ROC curve) parameters were used to evaluate the generated models. The highest values of Accuracy and AUROC are related to Adaptive Boosting and random forest algorithms, respectively.
Conclusion: Learning curves show that using different training examples and more complex selection of combination features improves the performance of the models. Further research is needed to evaluate the clinical effectiveness of machine learning models in a trial.
Materials and Methods: In this descriptive-applied study, the research population includes neonates admitted to the intensive care unit of Valiasr Hospital in Tehran and the research sample is the data of 4196 neonates admitted to this ward from 2016 to August, 2020. The initial features for creating a predictive model of sepsis were prepared by examining the relevant information sources and under the supervision of professors and officials of Valiasr Hospital's mother and fetus research center and its validity was confirmed by 5 neonatal professors of this hospital. In this research, machine learning algorithms have been used to create a sepsis prediction model.
Results: Accuracy and AUROC(area under the ROC curve) parameters were used to evaluate the generated models. The highest values of Accuracy and AUROC are related to Adaptive Boosting and random forest algorithms, respectively.
Conclusion: Learning curves show that using different training examples and more complex selection of combination features improves the performance of the models. Further research is needed to evaluate the clinical effectiveness of machine learning models in a trial.
Mohamad Jebraeily, Ali Rashidi, Taher Mohitmafi, Rooghayeh Muossazadeh,
Volume 14, Issue 6 (1-2021)
Volume 14, Issue 6 (1-2021)
Abstract
Background and Aim: Electronic prescription systems can improve patient safety and the quality of health care services. These systems must provide the capabilities required to reduce medical errors and enhance the performance of health care providers. The purpose of this study is to evaluate the capabilities of the e-prescription system from the perspective of physicians in the polyclinics of the Social Security Organization (SSO) of Urmia.
Materials and Methods: The present study is a descriptive cross-sectional study that was conducted in 2020. The study population consisted of 82 physicians working in 3 polyclinics of the SSO in Urmia, which was determined by census. The instrument used in this study is a self-designed questionnaire that the validity of it was determined based on the opinions of experts and its reliability was evaluated by Cronbach's alpha coefficient. Data analysis was performed using SPSS software.
Results: The results showed that in the section of documentation and access to information, the highest score was related to the possibility of drug prescribe (4.58), request for examination and radiology (4.44). In terms of decision support capabilities, the highest score for providing alerts related to drug interactions (4.18) and controlling the amount of medication prescribed for chronic patients (3.83) and also in the field of technical capabilities, the highest score related to easy to use (3.87) and fit of user interface (3.66).
Conclusion: The e-prescription system under survey has gained fewer score in some capabilities, such as access to pharmaceutical information based on reliable sources, advice to treatment options based on original diagnosis and the customized system. Therefore the system developer should be improved capabilities of it through communicating properly with users and understanding their real needs.
Materials and Methods: The present study is a descriptive cross-sectional study that was conducted in 2020. The study population consisted of 82 physicians working in 3 polyclinics of the SSO in Urmia, which was determined by census. The instrument used in this study is a self-designed questionnaire that the validity of it was determined based on the opinions of experts and its reliability was evaluated by Cronbach's alpha coefficient. Data analysis was performed using SPSS software.
Results: The results showed that in the section of documentation and access to information, the highest score was related to the possibility of drug prescribe (4.58), request for examination and radiology (4.44). In terms of decision support capabilities, the highest score for providing alerts related to drug interactions (4.18) and controlling the amount of medication prescribed for chronic patients (3.83) and also in the field of technical capabilities, the highest score related to easy to use (3.87) and fit of user interface (3.66).
Conclusion: The e-prescription system under survey has gained fewer score in some capabilities, such as access to pharmaceutical information based on reliable sources, advice to treatment options based on original diagnosis and the customized system. Therefore the system developer should be improved capabilities of it through communicating properly with users and understanding their real needs.
Niloofar Mohammadzadeh, Dr Seyed Hadi Sajjadi, Seyed Hasan Sajjadi,
Volume 15, Issue 1 (3-2021)
Volume 15, Issue 1 (3-2021)
Abstract
Background and Aim: Social networks that provide users with health data not only educate them but also play an active role in the health decision-making process. Health social networks, in addition to being a good tool for better patient communication with health care providers, can play an effective role in connecting similar patients with each other to receive social support. Social networking is one of the biggest achievements of Web 2, which facilitates communication between people. Despite the spread of social networks, their use in the field of health is still at its early levels. To implement an information system, it is first necessary to identify, design and model the related processes. The main purpose of this study was to provide technical documentation for the development of social networks in the field of health in order to facilitate future developments.
Materials and Methods: This study was an applied research. Due to the review of texts in the first phase, this research was descriptive. It is also a developmental research due to its technological dimensions in modeling and pattern model presentation. First, extracted features were confirmed based on experts’ opinions. Then, according to the identified features, social network modeling was performed at three levels of data, functional and process. Based on the modeling, a prototype model was designed and evaluated.
Results: In this research, technical documents were prepared for the development of social networks in the field of health in the three axes of data modeling, functional modeling and process modeling. In the usability assessment by Nielsen model, the created prototype based on modeling was evaluated. Finally, the number of problems in each case of the Nielsen model was determined. The case of "Visibility of system status" with 26.31 and "Consistency and standards" with 5.27 were associated with the highest and lowest problems, respectively.
Conclusion: The growing need and expansion of the use of social networks has created a good platform for using this tool in the field of health and exploiting its benefits. The present study focuses on providing technical documentation for the development of health social networks and to facilitate the development of social networks in the field of health.
Materials and Methods: This study was an applied research. Due to the review of texts in the first phase, this research was descriptive. It is also a developmental research due to its technological dimensions in modeling and pattern model presentation. First, extracted features were confirmed based on experts’ opinions. Then, according to the identified features, social network modeling was performed at three levels of data, functional and process. Based on the modeling, a prototype model was designed and evaluated.
Results: In this research, technical documents were prepared for the development of social networks in the field of health in the three axes of data modeling, functional modeling and process modeling. In the usability assessment by Nielsen model, the created prototype based on modeling was evaluated. Finally, the number of problems in each case of the Nielsen model was determined. The case of "Visibility of system status" with 26.31 and "Consistency and standards" with 5.27 were associated with the highest and lowest problems, respectively.
Conclusion: The growing need and expansion of the use of social networks has created a good platform for using this tool in the field of health and exploiting its benefits. The present study focuses on providing technical documentation for the development of health social networks and to facilitate the development of social networks in the field of health.
Nida Abdolahi, Mohamad Reza Nili Nili Ahmadabadi, Soghra Ebrahimi Qavam, Khadijeh Aliabadi, Mohammad Asgari,
Volume 15, Issue 1 (3-2021)
Volume 15, Issue 1 (3-2021)
Abstract
Background and Aim: Deep and sustainable learning requires a safe and healthy environment. Moreover, paying attention to the intertwined emotional, motivational, cognitive and social processes in the teaching-learning process is vital. Academic achievement motivation and self-regulated learning (SRL) are two important elements in this process that are influenced by the achievement emotions in the learning environment. Therefore, the aim of this study is to evaluate the effectiveness of instructional design model based on control-value theory of achievement emotions (CVT), on academic achievement motivation and self-regulation learning.
Materials and Methods: The research was quantitative and performed by Nonequlment design control group. The statistical population included female second year high school students in Tehran in the academic year of 1997-98, who were selected by multi-stage cluster random sampling in two experimental and control groups. The experimental group was trained according to the instructional design model based on CVT theory and the control group did not receive this training method. The questionnaire of academic achievement motivation and self-regulated learning was administered to the experimental and control groups as pre-test and post-test before and after the implementation of the model. Data were analyzed by inferential and descriptive statistics using SPSS software and multivariate covariance.
Results: The results of univariate analysis of covariance of group effect on the scores of dependent variables show that there is a significant difference between the experimental and control groups in cognitive strategy (F=11/94, P>0/05, η2=0/14), metacognition strategy (F=56/06, P>0/05, η2=0/44), motivational beliefs (F=6/36, P>0/05, η2=0/08) and academic achievement motivation (F=10/69, P>0/05, η2 =0/13).
Conclusion: The result of this study show that the use of instructional design model based on CVT theory has a positive effect on cognitive strategies, metacognition strategies, motivational beliefs and learners' academic achievement motivation.
Materials and Methods: The research was quantitative and performed by Nonequlment design control group. The statistical population included female second year high school students in Tehran in the academic year of 1997-98, who were selected by multi-stage cluster random sampling in two experimental and control groups. The experimental group was trained according to the instructional design model based on CVT theory and the control group did not receive this training method. The questionnaire of academic achievement motivation and self-regulated learning was administered to the experimental and control groups as pre-test and post-test before and after the implementation of the model. Data were analyzed by inferential and descriptive statistics using SPSS software and multivariate covariance.
Results: The results of univariate analysis of covariance of group effect on the scores of dependent variables show that there is a significant difference between the experimental and control groups in cognitive strategy (F=11/94, P>0/05, η2=0/14), metacognition strategy (F=56/06, P>0/05, η2=0/44), motivational beliefs (F=6/36, P>0/05, η2=0/08) and academic achievement motivation (F=10/69, P>0/05, η2 =0/13).
Conclusion: The result of this study show that the use of instructional design model based on CVT theory has a positive effect on cognitive strategies, metacognition strategies, motivational beliefs and learners' academic achievement motivation.
Faezeh Mahdizadeh, Fatemeh Mahdizadeh, Maryam Tatari, Mostafa Sheykhtayefeh,
Volume 15, Issue 2 (5-2021)
Volume 15, Issue 2 (5-2021)
Abstract
Background and Aim: Medical students, as the largest group of health care providers, should be able to combine their technical skills and professional knowledge to diagnose patients' problems and use it to take a big step towards reducing errors and increase the quality of care. For this reason, a study was conducted to investigate the relationship between health literacy and computer literacy among medical students in Torbat Heydariyeh in 2018.
Materials and Methods: This cross-sectional study with a descriptive-analytical approach was performed in the middle half of 2018 on 201 students of Torbat Heydariyeh University of Medical Sciences (THUMS), who were selected by multi-stage sampling method. Data were collected using the Iranian Adult Health Literacy Questionnaire (HELIA) and the Computer Literacy Questionnaire. Then, the data were analyzed with SPSS software, using descriptive statistics and Chi-square test.
Results: In this study, 175 subjects (87.1%) were female and the rest were male. The mean and standard deviation of age were 21.52±1.30 and 17.11±0/99, respectively. The results of multivariate linear regression showed that the variable dimensions of computer literacy could predict up to 63% of changes in students' health literacy score. The results also showed that the dimensions of basic skills, frequency of computer use and
self-assessment of working skills with Windows had a significant relationship with students' health literacy (P<0.05).
Conclusion: Considering the results, it is suggested that the necessary measures be taken to increase students' computer literacy by holding workshops and Update educational content in universities; in this way, a step towards increasing computer literacy and consequently, increasing the health literacy of students can be taken.
Materials and Methods: This cross-sectional study with a descriptive-analytical approach was performed in the middle half of 2018 on 201 students of Torbat Heydariyeh University of Medical Sciences (THUMS), who were selected by multi-stage sampling method. Data were collected using the Iranian Adult Health Literacy Questionnaire (HELIA) and the Computer Literacy Questionnaire. Then, the data were analyzed with SPSS software, using descriptive statistics and Chi-square test.
Results: In this study, 175 subjects (87.1%) were female and the rest were male. The mean and standard deviation of age were 21.52±1.30 and 17.11±0/99, respectively. The results of multivariate linear regression showed that the variable dimensions of computer literacy could predict up to 63% of changes in students' health literacy score. The results also showed that the dimensions of basic skills, frequency of computer use and
self-assessment of working skills with Windows had a significant relationship with students' health literacy (P<0.05).
Conclusion: Considering the results, it is suggested that the necessary measures be taken to increase students' computer literacy by holding workshops and Update educational content in universities; in this way, a step towards increasing computer literacy and consequently, increasing the health literacy of students can be taken.
Eng. Meisam Fallahnezhad, Reza Safdari,
Volume 15, Issue 3 (8-2021)
Volume 15, Issue 3 (8-2021)
Abstract
Background and Aim: Large amounts of hospital costs are not reimbursed annually by health insurance as deductions. Therefore, reducing deductions is very important for the hospital. In the study of design and implementation of analytical dashboard of insurance deductions based on medical intelligence business, to improve financial management with the aim of focusing on assessing the level of satisfaction and its applicability has been done.
Materials and Methods: To design the questionnaire, first 27 questions were prepared through library studies and interviews with members of the hospital board of directors, and the validity and consistency of its items were determined through content validity and Cronbach’s alpha coefficient. Data were analyzed in SPSS software and the results were used to design and implement the dashboard.
Results: The study is of development-applied type. In the first phase, to determine Content Validity Ratio CVI (Content Validity Index), and CVR (Content Validity Ratio) a researcher-made questionnaire was provided to 20 experts. In the second phase, by building a data warehouse in SQL (Structured Query Language), the information of the tables related to the deductions of the hospital HIS system was transferred to it and the operational information of the organization was extracted and converted into DW format and the map information was tested. OLAP (Online Analytical Processing) services were then loaded on the created analytics database. In the last step, Power BI tool was selected and used to create business intelligence mechanisms, display and visualize information. In the third phase, using the QUIS (Questionnaire for User Interface Satisfaction) standard questionnaire, the level of satisfaction and usability of the dashboard was evaluated by 15 experts.
Conclusion: In this study, two questionnaires were used. CVR was measured in all items of the first questionnaire, more than 0.50 and CVI was measured in the upper areas of 0.90 and Cronbach’s alpha coefficient was obtained between 0.8 and 0.9, which indicated a good level. The second questionnaire was to evaluate the level of satisfaction and usability of the dashboard that the average of the total evaluation based on the indicators of the QUIS questionnaire is equal to 85.40. Therefore, the level of satisfaction and usability of the dashboard was “very good” for the evaluators.
Materials and Methods: To design the questionnaire, first 27 questions were prepared through library studies and interviews with members of the hospital board of directors, and the validity and consistency of its items were determined through content validity and Cronbach’s alpha coefficient. Data were analyzed in SPSS software and the results were used to design and implement the dashboard.
Results: The study is of development-applied type. In the first phase, to determine Content Validity Ratio CVI (Content Validity Index), and CVR (Content Validity Ratio) a researcher-made questionnaire was provided to 20 experts. In the second phase, by building a data warehouse in SQL (Structured Query Language), the information of the tables related to the deductions of the hospital HIS system was transferred to it and the operational information of the organization was extracted and converted into DW format and the map information was tested. OLAP (Online Analytical Processing) services were then loaded on the created analytics database. In the last step, Power BI tool was selected and used to create business intelligence mechanisms, display and visualize information. In the third phase, using the QUIS (Questionnaire for User Interface Satisfaction) standard questionnaire, the level of satisfaction and usability of the dashboard was evaluated by 15 experts.
Conclusion: In this study, two questionnaires were used. CVR was measured in all items of the first questionnaire, more than 0.50 and CVI was measured in the upper areas of 0.90 and Cronbach’s alpha coefficient was obtained between 0.8 and 0.9, which indicated a good level. The second questionnaire was to evaluate the level of satisfaction and usability of the dashboard that the average of the total evaluation based on the indicators of the QUIS questionnaire is equal to 85.40. Therefore, the level of satisfaction and usability of the dashboard was “very good” for the evaluators.
Marsa Gholamzadeh, Seyed Mohammad Ayyoubzadeh, Hoda Zahedi, Sharareh Rostam Niakan Kalhori,
Volume 15, Issue 3 (8-2021)
Volume 15, Issue 3 (8-2021)
Abstract
Background and Aim: Due to the important role of radiological images for identifying patients with COVID-19, creating a model based on deep learning methods was the main objective of this study.
Materials and Methods: 15,153 available chest images of normal, COVID-19, and pneumonia individuals which were in the Kaggle data repository was used as dataset of this research. Data preprocessing including normalizing images, integrating images and labeling into three categories, train, test and validation was performed. By Python language in the fastAI library based on convolution technique (CNN) and four architectures (ResNet, VGG MobileNet, AlexNet), nine models through transitional learning method were trained to recognize patients from healthy persons. Finally, the performance of these models was evaluated with indicators such as accuracy, sensitivity and specificity, and F-Measure.
Results: Of the nine generated models, the ResNet101 model has the highest ability to distinguish COVID-19 cases from other cases with 95.29% sensitivity. Other applied models showed more than 96% accuracy in correctly diagnosis of various cases in test phase. Finally, the ResNet101 model was able to demonstrate 98.4% accuracy in distinguishing between healthy and infected cases.
Conclusion: The obtained accuracy showed the accurate performance of developed model in detecting COVID-19 cases. Therefore, by implementing an application based on the developed model, physicians can be helped in accurate and early diagnosis of cases. an application based on the developed model, physicians can be helped in accurate and early diagnosis of infected cases.
Materials and Methods: 15,153 available chest images of normal, COVID-19, and pneumonia individuals which were in the Kaggle data repository was used as dataset of this research. Data preprocessing including normalizing images, integrating images and labeling into three categories, train, test and validation was performed. By Python language in the fastAI library based on convolution technique (CNN) and four architectures (ResNet, VGG MobileNet, AlexNet), nine models through transitional learning method were trained to recognize patients from healthy persons. Finally, the performance of these models was evaluated with indicators such as accuracy, sensitivity and specificity, and F-Measure.
Results: Of the nine generated models, the ResNet101 model has the highest ability to distinguish COVID-19 cases from other cases with 95.29% sensitivity. Other applied models showed more than 96% accuracy in correctly diagnosis of various cases in test phase. Finally, the ResNet101 model was able to demonstrate 98.4% accuracy in distinguishing between healthy and infected cases.
Conclusion: The obtained accuracy showed the accurate performance of developed model in detecting COVID-19 cases. Therefore, by implementing an application based on the developed model, physicians can be helped in accurate and early diagnosis of cases. an application based on the developed model, physicians can be helped in accurate and early diagnosis of infected cases.
Arman Bahari, Behnoosh Moody,
Volume 15, Issue 4 (10-2021)
Volume 15, Issue 4 (10-2021)
Abstract
Background and Aim: Increasing the use of smartphones, improving the state of World Wide Web, and also the need for flexibility in the education process have made the implementation of e-learning in human society inevitable, eliminated time and space limitations, and provided equal education. However, the pace of its creation and development, especially in universities and higher education centers in developing countries such as Iran, is very slow. Therefore, the present study aims to investigate the factors affecting the creation and development of e-learning from the viewpoint of students of Zahedan University of Medical Sciences.
Materials and Methods: This is an applied and descriptive-survey study. The sample includes 313 students studying at Zahedan University of Medical Sciences during 2016-2017, who were selected by simple random sampling. Data were collected using a researcher-made questionnaire and analyzed using statistical tests and SPSS software.
Results: The findings show that the six selected factors of this study affect the creation and development of e-learning from the viewpoint of Zahedan University of Medical Sciences students. From the highest to the lowest effect, these factors include the quality of information and content (4.25), learners’ willingness (4.11), system quality (4.10), facilitators (4.05), student-professor interaction (3.98) and professor quality (3.84).
Conclusion: According to the findings of the present study, it can be concluded that policy makers and university administrators, considering the importance of each factor, invest and develop e-learning to provide better services to students and faculty.
Materials and Methods: This is an applied and descriptive-survey study. The sample includes 313 students studying at Zahedan University of Medical Sciences during 2016-2017, who were selected by simple random sampling. Data were collected using a researcher-made questionnaire and analyzed using statistical tests and SPSS software.
Results: The findings show that the six selected factors of this study affect the creation and development of e-learning from the viewpoint of Zahedan University of Medical Sciences students. From the highest to the lowest effect, these factors include the quality of information and content (4.25), learners’ willingness (4.11), system quality (4.10), facilitators (4.05), student-professor interaction (3.98) and professor quality (3.84).
Conclusion: According to the findings of the present study, it can be concluded that policy makers and university administrators, considering the importance of each factor, invest and develop e-learning to provide better services to students and faculty.
Mr Kasra Dolatkhahi, Adel Azar, Tooraj Karimi, Mohammad Hadizadeh,
Volume 15, Issue 4 (10-2021)
Volume 15, Issue 4 (10-2021)
Abstract
Background and Aim: Cancer and in particular Breast cancer are among the diseases that have the highest mortality rate in Iran after heart disease. The accurate prognosis for Breast cancer is important, and the presence of various symptoms and features of this disease makes it difficult for doctors to diagnose. This study aimed to identify the factors affecting Breast cancer, modeling and ultimately diagnosing the risk of Breast cancer.
Materials and Methods: In the present study, first, by content analysis and library studies, the effective factors in Breast cancer were identified, then with the help of a team of experts consisting of physicians and subspecialists in Breast oncology and Breast surgery; With the help of the Delphi method, the factors were adjusted and 26 final factors that were numerically correct and string based on local and climatic conditions were approved. Then, according to the final factors and based on the medical records of 5208 patients in the Cancer Research Center of Shahid Beheshti University of medical sciences, to diagnose cancer, Decision Tree, Random Forest, and Support Vector Machine methods were used as machine learning methods.
Results: In the first step, by content analysis method, 29 effective factors in Breast cancer were identified. Then, taking into account the indigenous and climatic conditions and using the Delphi method and also using the opinions of 18 Experts during three years, 26 factors were finalized. In the final step, using the medical records of the patients and the results obtained from the three methods mentioned, random forest, had the highest accuracy of 94.75% and precision of 97.26% in diagnosing Breast cancer. It has been noted that, compared to other similar studies, indigenous databases have been exploited, the accuracy obtained has been very close to previous studies, and in many cases much better.
Conclusion: Using the random forest method and taking advantage of the factors affecting Breast cancer, the ability to diagnose cancer has been provided with greatest accuracy.
Materials and Methods: In the present study, first, by content analysis and library studies, the effective factors in Breast cancer were identified, then with the help of a team of experts consisting of physicians and subspecialists in Breast oncology and Breast surgery; With the help of the Delphi method, the factors were adjusted and 26 final factors that were numerically correct and string based on local and climatic conditions were approved. Then, according to the final factors and based on the medical records of 5208 patients in the Cancer Research Center of Shahid Beheshti University of medical sciences, to diagnose cancer, Decision Tree, Random Forest, and Support Vector Machine methods were used as machine learning methods.
Results: In the first step, by content analysis method, 29 effective factors in Breast cancer were identified. Then, taking into account the indigenous and climatic conditions and using the Delphi method and also using the opinions of 18 Experts during three years, 26 factors were finalized. In the final step, using the medical records of the patients and the results obtained from the three methods mentioned, random forest, had the highest accuracy of 94.75% and precision of 97.26% in diagnosing Breast cancer. It has been noted that, compared to other similar studies, indigenous databases have been exploited, the accuracy obtained has been very close to previous studies, and in many cases much better.
Conclusion: Using the random forest method and taking advantage of the factors affecting Breast cancer, the ability to diagnose cancer has been provided with greatest accuracy.
Malihe Dalili Saleh, Maryam Salami, Faramarz Soheili, Soraya Ziaei,
Volume 15, Issue 4 (10-2021)
Volume 15, Issue 4 (10-2021)
Abstract
Background and Aim: University libraries must meet certain criteria to enter fourth-generation libraries, one of which is the use of new technologies. The aim of this study was to identify the attitudes of library users of medical universities towards the components of augmented reality (AR) technology.
Materials and Methods: The research method was survey and type of study was applied. Quantitative research approach and research tool was a researcher-made questionnaire. The internal validity of the questionnaire was assessed through CVI and its reliability was estimated using ICC. Validity of the questionnaire was confirmed using the opinions of 10 experts in information science and AR; its reliability was obtained with Cronbach’s alpha correlation coefficient (0.96). Through the online questionnaire, data from users’ perspectives on the components of familiarity, features, application, advantages, opportunities and limitations were collected in the form of 5 Likert questions. Data analysis with SPSS 26 was used through independent t-test, ANOVA and Tukey to evaluate the status of AR components.
Results: Users’ familiarity with AR was 50.55%. 78.23% of the users agreed with AR in the libraries of medical universities. In general, the mean was 3.91 and the standard deviation was 0.63. The possibility of developing research activities, use of technology to enhance learning, advantage of attractiveness, and opportunity to develop a scientific educational program were mentioned as the most important items among other AR factors. One of the limitations of setting it up in university libraries was the lack of high-speed internet. The general attitude of users towards AR was at the desired level.
Conclusion: Library users at medical universities agreed with the facilities, opportunities and use of AR. The results showed that AR technology is practical and useful from the perspective of users in the libraries of Iranian medical universities. AR with user support, improving user activity, creating attractiveness, attracting audience, content creation according to various library resources, content gamification, knowledge sharing, content resource deprivation, based on the availability of technical facilities, an opportunity to develop Creates libraries of medical universities.
Materials and Methods: The research method was survey and type of study was applied. Quantitative research approach and research tool was a researcher-made questionnaire. The internal validity of the questionnaire was assessed through CVI and its reliability was estimated using ICC. Validity of the questionnaire was confirmed using the opinions of 10 experts in information science and AR; its reliability was obtained with Cronbach’s alpha correlation coefficient (0.96). Through the online questionnaire, data from users’ perspectives on the components of familiarity, features, application, advantages, opportunities and limitations were collected in the form of 5 Likert questions. Data analysis with SPSS 26 was used through independent t-test, ANOVA and Tukey to evaluate the status of AR components.
Results: Users’ familiarity with AR was 50.55%. 78.23% of the users agreed with AR in the libraries of medical universities. In general, the mean was 3.91 and the standard deviation was 0.63. The possibility of developing research activities, use of technology to enhance learning, advantage of attractiveness, and opportunity to develop a scientific educational program were mentioned as the most important items among other AR factors. One of the limitations of setting it up in university libraries was the lack of high-speed internet. The general attitude of users towards AR was at the desired level.
Conclusion: Library users at medical universities agreed with the facilities, opportunities and use of AR. The results showed that AR technology is practical and useful from the perspective of users in the libraries of Iranian medical universities. AR with user support, improving user activity, creating attractiveness, attracting audience, content creation according to various library resources, content gamification, knowledge sharing, content resource deprivation, based on the availability of technical facilities, an opportunity to develop Creates libraries of medical universities.
Marjan Ghazi Saeedi, Mozhgan Tanhapour,
Volume 15, Issue 5 (1-2022)
Volume 15, Issue 5 (1-2022)
Abstract
Background and Aim: Telemedicine provides medical services remotely. There are some problems with implementing telemedicine projects. The purpose of this study was to investigate the most common telemedicine services in Iran and other developed countries as well as examine the legal, financial and privacy challenges of telemedicine services in these countries, especially in the era of the COVID-19 epidemic.
Material and Methods: In this study, the status of telemedicine in Iran and developed countries was reviewed. Thus, related papers and grey literature were retrieved from PubMed, Scopus, SID and Magiran scientific databases. Also, related websites including the Ministry of Health and Medical Education of the Islamic Republic of Iran were examined. According to the study’s purposes, the relevant resources were selected and summarized by researchers.
Results: Radiology, psychiatry and cardiology are the most widely used telemedicine services for interaction with patients as well as emergency, pathology and radiology for healthcare professional communication. Teleconsulting is the most widely used telemedicine service in Iran. There are some laws such as article 74 from section 14 in the Iran development plan to support the provision of e-health and telemedicine services. Also, there are some limited laws for patients’ privacy. In Europe, there is a set of guidelines for health websites, mobile health and cross-border exchange of health information, etc. although there are no uniform laws about telemedicine. HIPAA in the United States and GDPR in Europe are some privacy laws in developed countries. There are some restrictions on telemedicine reimbursement in the United States including the fee-for-service payment model; however, the costs of telemedicine in the United States are usually less than face-to-face treatment.
Conclusion: In the present era using telemedicine services become a requirement due to the outbreaks of epidemics such as COVID-19. Concerning the experience of developed countries, telemedicine services development in Iran requires some considerations in terms of legal, financial and privacy aspects including the creation of explicit laws on patients and healthcare provider’s rights, providing the telemedicine guidelines in different clinical fields such as structured formats for teleconsultation as well as the explicit laws for preserving the patient’s privacy.
Material and Methods: In this study, the status of telemedicine in Iran and developed countries was reviewed. Thus, related papers and grey literature were retrieved from PubMed, Scopus, SID and Magiran scientific databases. Also, related websites including the Ministry of Health and Medical Education of the Islamic Republic of Iran were examined. According to the study’s purposes, the relevant resources were selected and summarized by researchers.
Results: Radiology, psychiatry and cardiology are the most widely used telemedicine services for interaction with patients as well as emergency, pathology and radiology for healthcare professional communication. Teleconsulting is the most widely used telemedicine service in Iran. There are some laws such as article 74 from section 14 in the Iran development plan to support the provision of e-health and telemedicine services. Also, there are some limited laws for patients’ privacy. In Europe, there is a set of guidelines for health websites, mobile health and cross-border exchange of health information, etc. although there are no uniform laws about telemedicine. HIPAA in the United States and GDPR in Europe are some privacy laws in developed countries. There are some restrictions on telemedicine reimbursement in the United States including the fee-for-service payment model; however, the costs of telemedicine in the United States are usually less than face-to-face treatment.
Conclusion: In the present era using telemedicine services become a requirement due to the outbreaks of epidemics such as COVID-19. Concerning the experience of developed countries, telemedicine services development in Iran requires some considerations in terms of legal, financial and privacy aspects including the creation of explicit laws on patients and healthcare provider’s rights, providing the telemedicine guidelines in different clinical fields such as structured formats for teleconsultation as well as the explicit laws for preserving the patient’s privacy.
Samira Goharinejad, Sharareh Rostam Niakan Kalhori, Raheleh Salari, Mehdi Ebrahimi,
Volume 15, Issue 5 (1-2022)
Volume 15, Issue 5 (1-2022)
Abstract
Background and Aim: Diabetes Type II is a chronic metabolic disorder rising its prevalence worldwide. Self-care is the most important management strategy to control the disorder and its adverse effects. The aim of this study was to design and validate an assessment tool to determine the level of self-care of patients affected by Diabetes type II.
Materials and Methods: This study was a cross-sectional study. To conduct this study, based on reviewing the texts and reviewing the existing questionnaires, the proposed items were prepared and by eliminating and integrating similar items into a questionnaire in 4 areas related to diet, blood sugar monitoring, Physical activity, drug use was designed with 15 questions. Thirty patients with type 2 diabetes referred to the endocrinology clinic completed a questionnaire. The reliability of the questionnaire was assessed using Cronbach’s alpha and the validity of the questionnaire was assessed by content validity (CVR). Data were analyzed using SPSS software.
Results: The results showed that the mean and standard deviation of the age of the studied units was 52.4±12.51 years, of which 50% were female and the other 50% were male. 56% of them had type 2 diabetes for less than 5 years. Also, people with higher education had relatively better metabolic control in diabetes management and patients ‘answer to question 6 had the highest mean, which shows patients’ attention to blood sugar control. To determine the reliability of the questionnaire, Cronbach’s alpha coefficient for all questions was 0.773, with the omission of question 9, it was increased to 0.796. Only two validity questions were 0.66 and 0.16 which were excluded from the test. Pearson correlation coefficient was calculated for each question.
Conclusion: The results of this study showed that the questionnaire has the necessary validity and reliability. With this tool, appropriate advice can be provided to patients with type 2 diabetes in the field of self-care, including diet, medication, physical activity and blood sugar control to prevent the progression of the disease and its complications.
Materials and Methods: This study was a cross-sectional study. To conduct this study, based on reviewing the texts and reviewing the existing questionnaires, the proposed items were prepared and by eliminating and integrating similar items into a questionnaire in 4 areas related to diet, blood sugar monitoring, Physical activity, drug use was designed with 15 questions. Thirty patients with type 2 diabetes referred to the endocrinology clinic completed a questionnaire. The reliability of the questionnaire was assessed using Cronbach’s alpha and the validity of the questionnaire was assessed by content validity (CVR). Data were analyzed using SPSS software.
Results: The results showed that the mean and standard deviation of the age of the studied units was 52.4±12.51 years, of which 50% were female and the other 50% were male. 56% of them had type 2 diabetes for less than 5 years. Also, people with higher education had relatively better metabolic control in diabetes management and patients ‘answer to question 6 had the highest mean, which shows patients’ attention to blood sugar control. To determine the reliability of the questionnaire, Cronbach’s alpha coefficient for all questions was 0.773, with the omission of question 9, it was increased to 0.796. Only two validity questions were 0.66 and 0.16 which were excluded from the test. Pearson correlation coefficient was calculated for each question.
Conclusion: The results of this study showed that the questionnaire has the necessary validity and reliability. With this tool, appropriate advice can be provided to patients with type 2 diabetes in the field of self-care, including diet, medication, physical activity and blood sugar control to prevent the progression of the disease and its complications.
Reza Safdari, Seyyed Farshad Allameh, Ms Fariba Shabani,
Volume 15, Issue 6 (3-2022)
Volume 15, Issue 6 (3-2022)
Abstract
Background and Aim: Many risk factors can cause biliary system diseases. Hence, this category of diseases is amongst the most common ones. Active patient cooperation is very important in disease management, self-care, and clinical outcomes improvement. A mobile phone application has a high potential in supporting the patients’ self-management. Therefore, this study was conducted to recognize and define data elements to develop a self-care application for biliary patients.
Materials and Methods: The current descriptive study was conducted in 2 stages, resource investigation, and data elements’ need assessment. In the first stage, scientific articles available in databases were used for defining required data elements to develop the application for biliary patients, and a checklist of data elements was prepared. In the second stage, a questionnaire was made based on the checklist. Content and face validity were accepted by the research team and the reliability was calculated 87.2%, using the Cronbach’s alpha test. The mentioned questionnaire was given to Gastroenterologists at Imam Khomeini Hospital complex, and the elected data elements were recognized.
Results: In this application, data elements were categorized into seven sections, including demographic and clinical information, data related to the biliary system diseases, postoperative lifestyle information of the biliary patients, reminders, disease management, and informing. Sixty point five percent of the responders gave the highest importance to data elements in the demographic and clinical data section. Data elements related to patients’ education were considered highly important by 54.2% of the responders. Forty three point eight percent gave the highest importance to data elements in interventional applications’ sections, and only 4.2% gave the least importance to this section.
Conclusion: Based on the identified data elements, a self-care application was designed and developed and can be used as a supplement to specialized care for biliary patients.
Materials and Methods: The current descriptive study was conducted in 2 stages, resource investigation, and data elements’ need assessment. In the first stage, scientific articles available in databases were used for defining required data elements to develop the application for biliary patients, and a checklist of data elements was prepared. In the second stage, a questionnaire was made based on the checklist. Content and face validity were accepted by the research team and the reliability was calculated 87.2%, using the Cronbach’s alpha test. The mentioned questionnaire was given to Gastroenterologists at Imam Khomeini Hospital complex, and the elected data elements were recognized.
Results: In this application, data elements were categorized into seven sections, including demographic and clinical information, data related to the biliary system diseases, postoperative lifestyle information of the biliary patients, reminders, disease management, and informing. Sixty point five percent of the responders gave the highest importance to data elements in the demographic and clinical data section. Data elements related to patients’ education were considered highly important by 54.2% of the responders. Forty three point eight percent gave the highest importance to data elements in interventional applications’ sections, and only 4.2% gave the least importance to this section.
Conclusion: Based on the identified data elements, a self-care application was designed and developed and can be used as a supplement to specialized care for biliary patients.
Shahrbanoo Pahlevanynejad, Reza Safdari, Mojgan Rahmanian, Mohammad Saleh Safari,
Volume 16, Issue 1 (3-2022)
Volume 16, Issue 1 (3-2022)
Abstract
Background and Aim: Preeclampsia is one of the most serious cases of high-risk pregnancies that endanger women’s health worldwide, especially in developing countries. Preeclampsia is a specific pregnancy syndrome with a prevalence of about 7-14%, which is one of the three leading causes of death in pregnant women. Preeclampsia is the second most common cause of maternal mortality in Iran and accounts for 14% of maternal mortality. The present study was conducted to design, create and evaluate mobile-based preeclampsia self-care application.
Materials and Methods: This study was conducted in four stages to assess the needs of information elements, design, create and evaluate preeclampsia self-care application. In needs assessment step, 42 specialists, assistants and personnel related to the subject working in the Amir Al-Momenin (AS) Educational, Research and Treatment Center affiliated to Semnan University of Medical Sciences participated. The program was then initially evaluated by 7 physicians, and finally the suggestions provided by users in the design of the program were applied and the final version of the program was completed. The application was designed in the Android Studio environment and then its usability was evaluated using the opinions of 20 mothers and the QUIS tool.
Results: The information elements and functional capabilities required by the program were determined. In addition, the program established communication between the patient and the provider, also created the possibility of care management and control of the disease process. The performance of the program was evaluated by physicians and experts and then evaluated by pregnant mothers in terms of usability. The findings showed that users were satisfied with the application.
Conclusion: The use of mobile-based applications is a useful way to increase knowledge and promote the health of pregnant mothers and facilitate their access to medical information and acquire the necessary skills in their disease. This program helps pregnant mothers with preeclampsia to control their disease by observing proper nutrition and treatment principles to minimize the complications of their disease.
Materials and Methods: This study was conducted in four stages to assess the needs of information elements, design, create and evaluate preeclampsia self-care application. In needs assessment step, 42 specialists, assistants and personnel related to the subject working in the Amir Al-Momenin (AS) Educational, Research and Treatment Center affiliated to Semnan University of Medical Sciences participated. The program was then initially evaluated by 7 physicians, and finally the suggestions provided by users in the design of the program were applied and the final version of the program was completed. The application was designed in the Android Studio environment and then its usability was evaluated using the opinions of 20 mothers and the QUIS tool.
Results: The information elements and functional capabilities required by the program were determined. In addition, the program established communication between the patient and the provider, also created the possibility of care management and control of the disease process. The performance of the program was evaluated by physicians and experts and then evaluated by pregnant mothers in terms of usability. The findings showed that users were satisfied with the application.
Conclusion: The use of mobile-based applications is a useful way to increase knowledge and promote the health of pregnant mothers and facilitate their access to medical information and acquire the necessary skills in their disease. This program helps pregnant mothers with preeclampsia to control their disease by observing proper nutrition and treatment principles to minimize the complications of their disease.
Ahmad Siar Sadr, Roohollah Tavallaee, Mohammad Ali Afshar Kazemi,
Volume 16, Issue 1 (3-2022)
Volume 16, Issue 1 (3-2022)
Abstract
Background and Aim: Enterprise Architecture based on laboratory needs, and by using of the commons of valid and existing enterprise architecture frameworks, leads to the aligns of needs with organizational strategies and goals and information technology infrastructure. The aim of this study was the investigation of the effect of enterprise architecture model implementation on laboratory information management systems.
Materials and Methods: In this quantitative study in 2020, proposed enterprise architecture model which was based on the compilation of Zachman and service-oriented architecture models was investigated by the maturity of enterprise architecture at Sharif University. The statistical community of this study was 100 laboratory specialists based on Morgan sample determination table CCM (Capacity Maturity Model), which was designed based on the Likert spectrum, was used as a questionnaire assessment tool. For data analysis, descriptive indicators such as frequency, percentage and one-sample t-test to compare the mean in SPSS software was used.
Results: Assessing the maturity of enterprise architecture including four areas of IT (Information Technology) planning and organization, IT development and implementation, IT service and support, and IT monitoring and evaluation. Among the various dimensions of enterprise architecture maturity, the lowest average was related to the field of monitoring and evaluation and the highest average was related to the field of service and support. Dimensions in terms of status were: service and support dimension, planning and organizing dimension, development and implementation dimension, monitoring and evaluation dimension, respectively. The test results were significantly different in the areas related to the maturity of enterprise architecture, including the planning and organization areas, development and implementation, service and support (P<0.0001). There was no significant difference in monitoring and evaluation.
Conclusion: The use of enterprise architecture specific to laboratory management systems causes the optimal use of resources and ease of interaction. Evaluation of the implementation of the proposed architectural framework in the laboratory environment showed that the proposed model has matured in the three areas of planning and organization, development and implementation, service and support. In order to improve the maturity of enterprise architecture, more attention should be paid to the field of monitoring and evaluation and the reform program should start from this field.
Materials and Methods: In this quantitative study in 2020, proposed enterprise architecture model which was based on the compilation of Zachman and service-oriented architecture models was investigated by the maturity of enterprise architecture at Sharif University. The statistical community of this study was 100 laboratory specialists based on Morgan sample determination table CCM (Capacity Maturity Model), which was designed based on the Likert spectrum, was used as a questionnaire assessment tool. For data analysis, descriptive indicators such as frequency, percentage and one-sample t-test to compare the mean in SPSS software was used.
Results: Assessing the maturity of enterprise architecture including four areas of IT (Information Technology) planning and organization, IT development and implementation, IT service and support, and IT monitoring and evaluation. Among the various dimensions of enterprise architecture maturity, the lowest average was related to the field of monitoring and evaluation and the highest average was related to the field of service and support. Dimensions in terms of status were: service and support dimension, planning and organizing dimension, development and implementation dimension, monitoring and evaluation dimension, respectively. The test results were significantly different in the areas related to the maturity of enterprise architecture, including the planning and organization areas, development and implementation, service and support (P<0.0001). There was no significant difference in monitoring and evaluation.
Conclusion: The use of enterprise architecture specific to laboratory management systems causes the optimal use of resources and ease of interaction. Evaluation of the implementation of the proposed architectural framework in the laboratory environment showed that the proposed model has matured in the three areas of planning and organization, development and implementation, service and support. In order to improve the maturity of enterprise architecture, more attention should be paid to the field of monitoring and evaluation and the reform program should start from this field.
Leila Shahmoradi, Niloofar Kheradbin, Ahmad Reza Farzanehnejad, Niloofar Mohammadzadeh, Atefeh Ghanbari Jolfaei,
Volume 16, Issue 2 (5-2022)
Volume 16, Issue 2 (5-2022)
Abstract
Background and Aim: Identifying risk factors is recommended as the first step for depression management in children and adolescents. This study aims to determine the data elements required for developing a clinical decision support system for screening major depression in young people.
Materials and Methods: This research was a descriptive-analytical study. The research population included a variety of mental health specialists that were both psychologists and students in psychiatry and guidance & counseling majors as well as electronic databases including Scopus, Pubmed, Embase, PsychInfo, WOS and Clinical key. The data collection tool was a questionnaire designed in three main sections which was answered by a convenient sample of 8 people who were specialists in the field. To analyze the extracted data Content Validity Ratio (CVR) and Mean measures were calculated for each item in questionnaire. Content Validity Index (CVI) and Cronbach’s Alpha (using SPSS software) were calculated which were equal to 0.74 and 0.824 respectively which confirmed validity and reliability of the research tool.
Results: According to Lawshe’s table, data elements with CVR between 0 and 0.75 and Mean less than 1.5, like “Ethnicity and race” (CVR=-0.25, Mean=1.125), were rejected. Items such as “Gender” (CVR=0.5) with a CVR equal to or less than 0.75, as well as items with a CVR between 0 and 0.75 and a Mean equal to or more than 1.5, like “Marital status” (CVR=0.5, Mean=1.625) were retained and considered to be included as the minimum data set for screening major depression in ages 10 to 25 years. Data elements were categorized in three categories: Demographic, Clinical and Psychosocial
Conclusion: Clinical decision support systems can facilitate providing healthcare at different levels such as screening major depression. These systems can be used for screening major depression risk factors to improve accessibility to mental health practitioners, assure the implementation of guidelines and provide a common language between different levels of healthcare. Determining the minimum data set for screening major depression in ages 10 to 25 years, is the first step toward developing a clinical decision support system for screening individuals for major depression.
Materials and Methods: This research was a descriptive-analytical study. The research population included a variety of mental health specialists that were both psychologists and students in psychiatry and guidance & counseling majors as well as electronic databases including Scopus, Pubmed, Embase, PsychInfo, WOS and Clinical key. The data collection tool was a questionnaire designed in three main sections which was answered by a convenient sample of 8 people who were specialists in the field. To analyze the extracted data Content Validity Ratio (CVR) and Mean measures were calculated for each item in questionnaire. Content Validity Index (CVI) and Cronbach’s Alpha (using SPSS software) were calculated which were equal to 0.74 and 0.824 respectively which confirmed validity and reliability of the research tool.
Results: According to Lawshe’s table, data elements with CVR between 0 and 0.75 and Mean less than 1.5, like “Ethnicity and race” (CVR=-0.25, Mean=1.125), were rejected. Items such as “Gender” (CVR=0.5) with a CVR equal to or less than 0.75, as well as items with a CVR between 0 and 0.75 and a Mean equal to or more than 1.5, like “Marital status” (CVR=0.5, Mean=1.625) were retained and considered to be included as the minimum data set for screening major depression in ages 10 to 25 years. Data elements were categorized in three categories: Demographic, Clinical and Psychosocial
Conclusion: Clinical decision support systems can facilitate providing healthcare at different levels such as screening major depression. These systems can be used for screening major depression risk factors to improve accessibility to mental health practitioners, assure the implementation of guidelines and provide a common language between different levels of healthcare. Determining the minimum data set for screening major depression in ages 10 to 25 years, is the first step toward developing a clinical decision support system for screening individuals for major depression.
Mostafa Shanbehzadeh, Hadi Kazemi-Arpanahi, Raoof Nopour,
Volume 16, Issue 2 (5-2022)
Volume 16, Issue 2 (5-2022)
Abstract
Background and Aim: Breast cancer is one of the most common and aggressive malignancies in women. Timely diagnosis of breast cancer plays an important role in preventing the progression of this disease, timely treatment measures, and aftermath reducing the mortality rate of these patients. Machine learning has the potential ability to diagnose diseases quickly and cost-effectively. This study aims to design a CDSS based on the rules extracted from the decision tree algorithm with the best performance to diagnose breast cancer in a timely and effective manner.
Materials and Methods: The data of 597 suspected people with breast cancer (255 patients and 342 healthy people) were retrospectively extracted from the electronic database of Ayatollah Taleghani Hospital in Abadan city with 24 characteristics, mainly pertained to lifestyle and medical histories. After selecting the most important variables by using the Chi-square Pearson and one-way analysis of variance (P<0.05), the performance of selected data mining algorithms including RF, J-48, DS, RT and XG -Boost was evaluated for breast cancer diagnosis in Weka 3.4 software. Finally, the breast cancer diagnostic system was designed based on the best model and through C# programming language and Dot Net Framework V3.5.4.
Results: Fourteen variables including personal history of breast cancer, breast sampling, and chest X-ray, high blood pressure, increased LDL blood cholesterol, presence of mass in upper inner quadrant of the breast, hormone therapy with estrogen, hormone therapy with Estrogen-progesterone, family history of breast cancer, age, history of other cancers, waist-to-hip ratio and fruit and vegetable consumption showed a significant relationship with the output class at the P<0.05. Based on the results of the performance evaluation of selected algorithms, the RF model with sensitivity, specificity, accuracy, and F- measure equal to 0.97, 0.99, 0.98, 0.974, respectively, AUC=0.936 had higher performance than other selected algorithms and was suggested as the best model for breast cancer diagnosis.
Conclusion: It seems that using modifiable variables such as lifestyle and reproductive-hormonal characteristics as input to the RF algorithm to design the CDSS, can detect breast cancer cases with optimal accuracy. In addition, the proposed system can be effectively adapted in real clinical environments for quick and effective disease diagnosis.
Materials and Methods: The data of 597 suspected people with breast cancer (255 patients and 342 healthy people) were retrospectively extracted from the electronic database of Ayatollah Taleghani Hospital in Abadan city with 24 characteristics, mainly pertained to lifestyle and medical histories. After selecting the most important variables by using the Chi-square Pearson and one-way analysis of variance (P<0.05), the performance of selected data mining algorithms including RF, J-48, DS, RT and XG -Boost was evaluated for breast cancer diagnosis in Weka 3.4 software. Finally, the breast cancer diagnostic system was designed based on the best model and through C# programming language and Dot Net Framework V3.5.4.
Results: Fourteen variables including personal history of breast cancer, breast sampling, and chest X-ray, high blood pressure, increased LDL blood cholesterol, presence of mass in upper inner quadrant of the breast, hormone therapy with estrogen, hormone therapy with Estrogen-progesterone, family history of breast cancer, age, history of other cancers, waist-to-hip ratio and fruit and vegetable consumption showed a significant relationship with the output class at the P<0.05. Based on the results of the performance evaluation of selected algorithms, the RF model with sensitivity, specificity, accuracy, and F- measure equal to 0.97, 0.99, 0.98, 0.974, respectively, AUC=0.936 had higher performance than other selected algorithms and was suggested as the best model for breast cancer diagnosis.
Conclusion: It seems that using modifiable variables such as lifestyle and reproductive-hormonal characteristics as input to the RF algorithm to design the CDSS, can detect breast cancer cases with optimal accuracy. In addition, the proposed system can be effectively adapted in real clinical environments for quick and effective disease diagnosis.
Saman Mohammadpour, Reza Rabiei, Elham Shabahrami, Kamyar Fathisalari, Maryam Khakzad, Mostafa Langarizadeh,
Volume 16, Issue 2 (5-2022)
Volume 16, Issue 2 (5-2022)
Abstract
Background and Aim: Cancer is the second leading cause of death in the world, which leads to the death of more than 10 million people in the world every year. Its early diagnosis, management and proper treatment play an important role in reducing complications and mortality. One of the support tools in early diagnosis, treatment and management of this disease are Clinical Decision Support System (CDSS), which are divided into two groups, rule-based and non-rule-based. Rule-based decision support systems are created based on clinical guidelines, while non-rule-based decision support systems use machine learning. In this research, the effects of decision support systems, rule-based and non-rule-based, on cancer diagnosis, treatment and management were measured.
Materials and Methods: The present study was conducted using a systematic review method, which was conducted by searching the Web of Science, Scopus, IEEE and PubMED databases until 12/31/2021. After removing duplicates and evaluating the characteristics of the inclusion and exclusion criteria, studies related to the goal were selected. The selection of articles was based on the title, abstract and full text The data collection tool was the data extraction form, which included year of study, type of study, system of body, organ of body, the service provided by the decision support system, type of decision support system, effect, effect index and the score of effect index. Narrative synthesis were used for data analysis.
Results: Out of 768 articles, 16 articles related to the objectives of the study were identified. Studies were presented in two categories of clinical decision-support systems: Rule-based and non-Rule based. The effects evaluated in the clinical decision support systems were Rule-based, dose adjustment, symptoms, adherence to treatment guidelines, care time, smoking, need for chemotherapy and pain management, all of which except pain management were significant and positive. The effects evaluated were in the category of non-Rule based clinical decision support systems, diagnostic and therapeutic decisions, controlling neutropenia, all of which were significant and positive except controlling neutropenia.
Conclusion: The results obtained for the effectiveness of both Rule-based and non-Rule-based decision support systems indicated different benefits of these two categories. Therefore, using their combination in the field of cancer can bring very useful results.
Materials and Methods: The present study was conducted using a systematic review method, which was conducted by searching the Web of Science, Scopus, IEEE and PubMED databases until 12/31/2021. After removing duplicates and evaluating the characteristics of the inclusion and exclusion criteria, studies related to the goal were selected. The selection of articles was based on the title, abstract and full text The data collection tool was the data extraction form, which included year of study, type of study, system of body, organ of body, the service provided by the decision support system, type of decision support system, effect, effect index and the score of effect index. Narrative synthesis were used for data analysis.
Results: Out of 768 articles, 16 articles related to the objectives of the study were identified. Studies were presented in two categories of clinical decision-support systems: Rule-based and non-Rule based. The effects evaluated in the clinical decision support systems were Rule-based, dose adjustment, symptoms, adherence to treatment guidelines, care time, smoking, need for chemotherapy and pain management, all of which except pain management were significant and positive. The effects evaluated were in the category of non-Rule based clinical decision support systems, diagnostic and therapeutic decisions, controlling neutropenia, all of which were significant and positive except controlling neutropenia.
Conclusion: The results obtained for the effectiveness of both Rule-based and non-Rule-based decision support systems indicated different benefits of these two categories. Therefore, using their combination in the field of cancer can bring very useful results.
Reza Abbasi, Fatemeh Rangraz Jeddi, Shima Anvari, Reza Khajouei,
Volume 16, Issue 3 (8-2022)
Volume 16, Issue 3 (8-2022)
Abstract
Background and Aim: Hospital managers are one of the key decision-makers in the implementation of health information systems. This study aimed to determine the implementation challenges of health information systems based on the hospital managers’ perspective.
Materials and Methods: This descriptive-analytical study was conducted in 2019 on the hospital managers of three provinces (Kerman, Yazd, Sistan and Baluchestan). Data were collected using a self-administrated questionnaire. The face validity of this questionnaire was approved by experts in health informatics and health information management and its reliability was confirmed by Cronbach’s alpha (α=96.7%). Data were analyzed using SPSS. To investigate the relationship between the mean of each challenge with demographic variables, Pearson, Independent T-test, and ANOVA tests were used.
Results: In this study, the factors related to ignoring the hospital manager’s needs in system selection (1.333 out of 2 points), hardware purchase cost, insufficient user training to using the system (1.238), inadequate manpower and health informatics specialists (1.19), software purchase cost, insufficient financial resources (1.142), high cost of system launching, the lack of integration and interoperability among information systems, lack of support from health care professionals (1.047), and lack of management experience in choosing the best system (one out of 2) had the highest scores (out of 2 points). Also, personnel training costs to work with the system (-0.092) and Lack of improvement in work processes (-0.047) obtained the lowest scores. Data analysis showed that managers with clinical backgrounds considered financial and human challenges more important than non-clinical managers (P<0.031).
Conclusion: The hospital managers believed that financial, human, technical, managerial, and organizational factors are the most important challenges in implementing health information systems in Iran’s hospitals respectively. The health policy-makers and planners at large and small levels can address many of the challenges before implementing systems by focusing on identified priorities.
Materials and Methods: This descriptive-analytical study was conducted in 2019 on the hospital managers of three provinces (Kerman, Yazd, Sistan and Baluchestan). Data were collected using a self-administrated questionnaire. The face validity of this questionnaire was approved by experts in health informatics and health information management and its reliability was confirmed by Cronbach’s alpha (α=96.7%). Data were analyzed using SPSS. To investigate the relationship between the mean of each challenge with demographic variables, Pearson, Independent T-test, and ANOVA tests were used.
Results: In this study, the factors related to ignoring the hospital manager’s needs in system selection (1.333 out of 2 points), hardware purchase cost, insufficient user training to using the system (1.238), inadequate manpower and health informatics specialists (1.19), software purchase cost, insufficient financial resources (1.142), high cost of system launching, the lack of integration and interoperability among information systems, lack of support from health care professionals (1.047), and lack of management experience in choosing the best system (one out of 2) had the highest scores (out of 2 points). Also, personnel training costs to work with the system (-0.092) and Lack of improvement in work processes (-0.047) obtained the lowest scores. Data analysis showed that managers with clinical backgrounds considered financial and human challenges more important than non-clinical managers (P<0.031).
Conclusion: The hospital managers believed that financial, human, technical, managerial, and organizational factors are the most important challenges in implementing health information systems in Iran’s hospitals respectively. The health policy-makers and planners at large and small levels can address many of the challenges before implementing systems by focusing on identified priorities.
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