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Showing 5 results for Radiology

Smh Mousavi, F Faraji Khiavi, R Sharifian, G Shaham,
Volume 3, Issue 3 (3-2010)
Abstract

Background and Aim: Because of preventing of radiation damages, special safety issues are considered in radiology departments: But, the other safety aspect issues are not observed regularly. As an important part of safety plan, radiology departments should be assessed from physical, building design aspects and cope with fire.

Materials and Methods: This descriptive study was directed as a cross sectional research. Tehran University of Medical Sciences hospitals radiology department were assessed for standards of physical spaces, radiation preventing, and cope with fire, patient's and staff safety.A Check-list was used as data collection instrument.Each safety issue estimated as safe (>80%), not safe (<50%) and relatively safe (between 50 and 80 %).

Results: Overall, safety standards were observed in Tehran university of Medical Sciences Hospitals Departments,with relatively safe standards regarding patient's safety and cope with fire.

Conclusions: Fire protocols must be regarded in radiology wards in hospitals. Appropriate designing and programming which considers patient's safety from the time of  entering to radiology ward until leaving is offered.


Aram Rostami, Hamid Bourghi, Reza Ghasemnejad,
Volume 7, Issue 6 (3-2014)
Abstract

 Background and Aim: X-Ray departments are among the most essential and expensive parts of any healthcare organization. Meanwhile, the proper application of hospital information systems (HIS) leads to the quality enhancement of health services and to the cost reduction of medical departments. The purpose of this study is to evaluate the knowledge of radiology department staffs in hospitals affiliated to Hamadan University of Medical Sciences (HUMS) about HIS applications.

 Materials and Methods: In this descriptive research (2012), the knowledge of radiology department staffs in HUMS hospitals was studied using a two-part questionnaire including a demographic part and standard items to evaluate the HIS knowledge of radiology department staffs. Finally, the obtained data were analyzed statistically by SPSS (version 17).

 Results: The results showed that 3.8% of staff members had a weak awareness, 65.4% an average awareness, and 30.8% a good awareness about HIS applications. Perfect awareness was not observed in this study.

 Conclusion: According to the results of this study, running related and up-to-date courses for staff members working in radiology departments is recommended. 

 


Maryam Ahmadi, Azadeh Bashiri,
Volume 8, Issue 2 (7-2014)
Abstract

 Background and Aim: In order to better design an electronic health record system in the country, determining standardized data elements for creating an integrated information system is important. In this study, the minimum data set of radiology reporting system is determined.

 Materials and Methods: In this descriptive cross-sectional study, 13 radiologists, 3 anesthesiologists, 3 general practitioners and 3 insurance experts working in the Imaging Center of Imam Khomeini hospital in Tehran were chosen. The research tool was a questionnaire having 11 parts. Content validity and test-retest method were used to measure the validity and reliability of the questionnaire, respectively. Data analysis was performed using the SPSS software.

 Results: The highest means reported were radiologists' written explanations and suggestions (9.6), image interpretation (9.5), the name of contrast material (9.4), the name of imaging procedure (9.3) type and date of previous measures (9.1), and the final diagnosis (9) and the lowest averages belonged to referring physician's address (4.8), relationship between patients and the primary individual insured (4.3), and religion (2.2).

 Conclusion: In an electronic health record system, due to the importance of radiology reports for the diagnosis and future management of a patient's clinical problems, it is necessary to pay attention to the minimum set of data related to these reports such as administrative, insurance, patient identity, and clinical data, and the results of radiological examinations for exchanging with electronic health record system.

 


Hossein Rahanjam, Hossein Qeraati, Mohammad Reza Kardan,
Volume 10, Issue 4 (9-2016)
Abstract

Background and Aim: One of the main steps of optimization process in diagnostic imaging is quality control of X-ray devices. If the control quality process and the quality of X-ray equipment are not ensured through a systematic procedure, it can increase the risk of unnecessary exposures among the population. Therefore, this study can reduce the risk of unnecessary exposures in the entire population. 
Materials and Methods: In this study, six quality control tests including voltage measurement accuracy test, time accuracy test, output repeatability test, output to time linearity test, output to milliamp linearity test, and radiation quality measurement test were evaluated in all centers of Ilam in accordance with what the international Atomic Energy Agency and the Atomic Energy Organization of Iran has presented. 
Results: The result showed that diagnostic X-ray devices available in Ilam had a relatively good quality in all quality control tests that were done except the associated with the radiance quality of (HVL). However, almost all these devices need to add additional filters to the X-ray tubes to resolve error in their HVL. 
Conclusion: Adding additional filters to radiology devices in Ilam Province and modifying the thickness of filters seem to be necessary and desirable which will prevent the unnecessary increase in patients' dose. The accurate and regular implementation of quality control tests in imaging wards should change into a culture. On the other hand, the relevant organizations which have the great responsibility to protect people against radiation are recommended to monitor and supervise radiology centers more accurately and responsibly to repair diagnostic radiation devices.


Seyed Mohammad Sadegh Dashti, Amid Khatibi Bardsiri, Mehdi Jafari Shahbazzadeh,
Volume 18, Issue 1 (3-2024)
Abstract

Background and Aim: Medical reports and electronic health records are critically important for diagnosis, treatment, patient protection, and medical research. Correcting spelling errors in medical texts is essential to ensure accurate interpretation of information. This research was conducted to automatically correct spelling mistakes in Persian medical texts using neural networks.
Material and Methods: In this study, which was conducted in 2023, a computational model based on artificial intelligence neural networks and dual embedding techniques was developed using Python in a Windows environment. The dual embedding model was fine-tuned for correcting spelling errors in Persian sonography texts. The proposed model employs various techniques for automatic error detection, including dictionary lookup approach and contextual similarity coefficients. Furthermore, features specific to text processing, such as Edit-Distance, along with similarity coefficients, were utilized to automatically select the most appropriate substitute for a misspelled word. The training and testing data for the current model were sourced from a collection of sonography texts from the Imam Khomeini Hospital’s sonography clinic in Tehran.
Results: The proposed model which is based on artificial neural networks, leverages a novel dualembedding architecture to select the best candidate words for correcting both non-word and real-word errors. According to the evaluation results on Persian sonography text, the proposed model achieved an F-Measure accuracy of 90.5% in detecting real-word errors. Furthermore, it demonstrated an impressive 90% accuracy in automatically correcting these real-word errors. Additionally, the model exhibited a strong performance, achieving 90.8% accuracy in correcting non-word errors.
Conclusion: Based on the evaluation results, the proposed method is robust against various changes in word forms and can effectively manage a wide range of morphological and semantic errors, including replacements, transpositions, insertions, and deletions in medical texts. The integration of EditDistance with textual similarity coefficients extracted from the dual embedding model significantly enhanced the accuracy of spelling corrections in Persian sonography texts, ensuring greater validity of such documents. The authors believe that the proposed model represents a significant advancement in the detection and correction of spelling errors in Persian sonography texts.


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