Search published articles


Showing 6 results for Classification
Comparison of Cardiovascular Diseases Classification in some developed countries with Iran
R Safdari , M Maleki , V Ghorbani ,
Volume 3, Issue 2 (9-2009)
Abstract

Background and Aim: Today, cardiovascular diseases are the most important public health challenges in the world. Prevention and management of cardiovascular diseases necessitate the existence of a comprehensive system for recording data. Patient medical document is one of the most important data which should be classified so to facilitate and expedite the treatment process. A comparison of cardiovascular disease classification systems could assist health care policy makers to battle cardiovascular diseases.

Materials and Methods: This descriptive-comparative study conducted during years 2007-2008. The cardiovascular diseases classification systems in USA, Australia, England and Canada were reviewed. Data collecting was done through literature review, Internet and e-mail.

Results : The cardiovascular disease classification systems of all the developed countries are national. The developed countries, with the exception of England, utilize a multiracial classification model, especially designed to reflect the individual requirements of every single one of them. This model employs health care standards, e-learning, annual educational programs, and consultation with experts. Iran lacks such a national classification system for cardiovascular diseases.

Discussion and Conclusion : In order to improve the management and prevention of cardiovascular diseases in Iran, it is essential that the cardiovascular disease classification system in the country be national.


Work-To-Work Bibliographic Relationships In Medical Subject Areas Based On Functional Requirements For Bibliographic Records (FRBR) During 2006-2010
Masoud Mohammadi , Seyed Javad Ghazi Mir Saeed , Alireza Noruzi ,
Volume 7, Issue 4 (11-2013)
Abstract

Background and Aim: FRBR is one of the models considered in cataloging and work-to-work relationships are introduced as types of bibliographic relationships present in this model.

This study examines the distribution of dispersion relationships in medical subject areas based on FRBR model in Persian medical sources published from 2006 to 2010.

Materials and Methods: This study is a descriptive survey . Data were obtained from Iranian OPAC ( online public access catalog) . To determine the areas of medical sciences, both LC (Library of Congress) and Dewey Classifications were applied. For data analysis, Excel 2007 was used. Using descriptive statistics, the researcher presented the results in the form of tables and graphs.

Results: According to Dewey Classification, ‘diseases’ was the subject area having the highest number of bibliographic relationships and the lowest frequency belonged to ‘experimental medicine’. The analysis based on LC Classification, however, showed that ‘internal medicine’ had the highest number of bibliographic relationships Botanic, Thomsonian, Eclectic Medicine, Chiropractic and Alternative medicine subject matters had the lowest bibliographic relationships.

Conclusion : Distribution of work-to-work bibliographic relationships in Persian medical sources based on Dewey and LC Classifications is heterogeneous. Despite the obtained apparently heterogeneous results, such a difference cannot be due to differences in the frequency of bibliographic relationships of medical topics because the classification criteria of medical sciences are different in these two systems.


Determination Of Breast Density Using Fuzzy Logic
Mostafa Langarizadeh, Rozi Mahmud,
Volume 8, Issue 3 (9-2014)
Abstract

 Background and Aim: The risk of breast cancer increases directly in line with breast density. Therefore, it is important to pay more attention to denser breasts in order to detect abnormalities. The aim of this paper was to design and suggest a quantitative method to categorize breast density in digital mammogram images using fuzzy logic.

 Materials and Methods: This was a crosectional study which resulted in developing a new system. The research population was including patients who undergo mammography in National Cancer Society of Malaysia during 2010 to 2011. Sample included 220 mammogram images which was selected randomly. Data analysis was done using SPSS with Kappa statistics.

 Results: Accuracy level of 92.8% was obtained based on evaluation of the system and there was a strong correlation between the system output and radiologists’ estimation (K=0.87, p=0.0001).

 Conclusion : Results obtained from the suggested system had higher performance than similar systems. Therefore, it could be concluded that the fuzzy logic may be used in this area. In addition, such systems could be helpful for physicians.


Comparison of Data Classification Algorithms to Determine the Type of Neonatal Jaundice
Reza Safdari, Maliheh Kadivar, Parinaz Tabari, Hala Shawky Own ,
Volume 11, Issue 5 (1-2018)
Abstract
Background and Aim: Neonatal jaundice is a matter that is very important for clinicians all over the world because this disease is one of the most common cases that requires clinical care. The aim of this study is to use data classification algorithms to predict the type of jaundice in neonates, and therefore, to prevent irreparable damages in future.
Materials and Methods: This is a descriptive study and is done with the use of neonatal jaundice dataset that has been collected in Cairo, Egypt. In this study, after preprocessing the data, classification algorithms such as decision tree, Naïve Bayes, and kNN (k-Nearest Neighbors) were used, compared and analyzed in Orange application.
Results: Based on the findings, decision tree with precision of 94%, Naïve Bayes with precision of 91%, and kNN with precision of 89% can classify the types of neonatal jaundice. So, among these types, the most precise classification algorithm is decision tree. 
Conclusion: Classification algorithms can be used in clinical decision support systems to help physicians make decisions about the types of special diseases; therefore, physicians can look after patients appropriately. So the probable risks for patients can be decreased. 

Coding System Design for Medicines and Medical Devices in Iran
Reza Safdari, Seyed Sina Marashi Shooshtari, Marzieh Esmaeili, Fozieh Tahmasbi, Zohreh Javanmard,
Volume 13, Issue 6 (2-2020)
Abstract
Background and Aim: The importance of managing medicines and medical devices as vital resources in healthcare industry cannot be ignored. Therefore, the application of coding systems could be of great help in the control of the required processes. This study aims to develop a coding system for medicines and medical devices in Iran.
Materials & Methods: This descriptive study was planned to be carried out in four phases from September 2018 to August 2019. To identify the requirements of designing a coding system for the classification of medicines and medical devices, library resources were studied, and the existing coding systems in the area of medicines and medical devices came under scrutiny. Then, based on the expert opinion on the results, the initial model of the coding system was designed.
Results: Thirty-five coding systems were identified and investigated. To design the proposed system, two coding systems -- ATC/DDD and UMDNS -- were selected as a core for medicines and medical devices, respectively. Then, based on expert opinion, the axes for the place of consumption and the placement of products and also the application of Quick Response (QR) code for data encoding were added.
Conclusion: The design and development of a comprehensive coding system–which is in compliance with the international protocols and capable of including both medicines and medical devices simultaneously – could be very helpful. Besides, using the location axis in the structure of coding system can improve the management of these products.

Asthma Control Level Assessment by Moving from the Current Reactive Care Models into a Preventive Approach based on Fuzzy Clustering and Classification Algorithms
Roghaye Khasha, Mohammad Mahdi Sepehri, Nasrin Taherkhani,
Volume 14, Issue 3 (7-2020)
Abstract
Background and Aim: Asthma is a common and chronic disease of respiratory tracts. The best way to treat Asthma is to control it. Experts of this field suggest the continues monitoring on Asthma symptoms and adjustment of self-care plan with offering the preventive treatment program to have desired control over Asthma. Presenting these plans by the physician is set based on the control level in which the patient is. Therefore, successful recognition and classification of the disease control level can play an important role in presenting the treatment program to the patient and improves the self-care and strengthens the early interventions to alleviate the Asthma symptoms.  
Materials and Methods: Based on this objective, we collected the data of 96 Asthma patients within a 9-month period from a specialized hospital for pulmonary diseases in Tehran. Then we classified the Asthma control level by fuzzy clustering and different types of data mining method within a multivariate dataset with the multi-class response variable.
Results: Our best model resulting from the balancing operations and feature selection on data have yielded the accuracy of 88%.
Conclusion: Our proposed model can be applied in electronic Asthma self-care systems to support the decision in real time and personalized warnings on the possible deterioration of Asthma control. Such tools can centralize the Asthma treatment from the current reactive care models into a preventive approach in which the physician’s decisions and therapeutic actions are resulting from the personal patterns of chronic Asthma control and prevention of acute Asthma.

Page 1 from 1     

© 2026 , Tehran University of Medical Sciences, CC BY-NC 4.0

Designed & Developed by: Yektaweb