Volume 16, Issue 6 (Feb 2023)
payavard 2023, 16(6): 504-514 |
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Ethics code: IR.BUMS.REC.1401.066
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Bahador F, Sabahi A, Jalali S, Ameri F. Investigating the Role of Artificial Intelligence in Management of Diabetes in Iran: A Systematic Review. payavard 2023; 16 (6) :504-514
URL: http://payavard.tums.ac.ir/article-1-7306-en.html
URL: http://payavard.tums.ac.ir/article-1-7306-en.html
1- Ph.D. Candidate in Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran
2- Assistant Professor, Department of Health Information Technology, Ferdows School of Health and Allied Medical Sciences, Birjand University of Medical Sciences, Birjand, Iran
3- Bachelor of Science in Health Information Technology, Ferdows School of Health and Allied Medical Sciences, Birjand University of Medical Sciences, Birjand, Iran
4- Master of Sciences Student in Health Information Technology, Student Research Committee, School of Paramedical and Rehabilitation, Mashhad University of Medical Sciences, Mashhad, Iran ,AmeriF4012@mums.ac.ir
2- Assistant Professor, Department of Health Information Technology, Ferdows School of Health and Allied Medical Sciences, Birjand University of Medical Sciences, Birjand, Iran
3- Bachelor of Science in Health Information Technology, Ferdows School of Health and Allied Medical Sciences, Birjand University of Medical Sciences, Birjand, Iran
4- Master of Sciences Student in Health Information Technology, Student Research Committee, School of Paramedical and Rehabilitation, Mashhad University of Medical Sciences, Mashhad, Iran ,
Abstract: (2300 Views)
Background and Aim: Diabetes is one of the most common metabolic diseases in Iran and the fifth leading cause of death all over the world. Its spread around the world has created new methods in biomedical research, including artificial intelligence. The present study was carried out to review the studies conducted in the area of artificial intelligence and diabetes in Iran.
Materials and Methods: This study was carried out using a systematic review method. Valid domestic databases, including Irandoc, Magiran, Sid and Google Scholar search engine, were reviewed using the keywords of artificial intelligence and diabetes in Persian both individually and in a combined manner without time limitation until June 20, 2021. A total number of 7495 articles were retrieved, which were screened in different stages (exclusion of duplicates (1824), title and summary of the articles (5884) and full text (30) and finally 20 articles that met the criteria desired by the researchers were carefully reviewed.
Results: Among the retrieved articles, 20 articles met the inclusion criteria, of which 16 articles dealt with methods based on artificial intelligence and 4 articles dealt with the design of new systems based on artificial intelligence. Also, 10 articles examined the role of artificial intelligence in prediction, 8 articles in diagnosis, and 2 articles dealt with the control and management of diabetes. Most of the articles were related to the use of data mining methods such as artificial neural network, decision tree, etc. (16 articles). Some studies also evaluated and compared artificial intelligence methods on application, accuracy and the sensitivity of artificial intelligence in diagnosing and predicting diabetes (10 studies).
Conclusion: A systematic review of articles revealed that the use of data mining methods for diabetes management in Iran has been associated with good progress, but there is a need to design artificial intelligence systems and algorithms and more measures should be taken in the area of diabetes control and management.
Materials and Methods: This study was carried out using a systematic review method. Valid domestic databases, including Irandoc, Magiran, Sid and Google Scholar search engine, were reviewed using the keywords of artificial intelligence and diabetes in Persian both individually and in a combined manner without time limitation until June 20, 2021. A total number of 7495 articles were retrieved, which were screened in different stages (exclusion of duplicates (1824), title and summary of the articles (5884) and full text (30) and finally 20 articles that met the criteria desired by the researchers were carefully reviewed.
Results: Among the retrieved articles, 20 articles met the inclusion criteria, of which 16 articles dealt with methods based on artificial intelligence and 4 articles dealt with the design of new systems based on artificial intelligence. Also, 10 articles examined the role of artificial intelligence in prediction, 8 articles in diagnosis, and 2 articles dealt with the control and management of diabetes. Most of the articles were related to the use of data mining methods such as artificial neural network, decision tree, etc. (16 articles). Some studies also evaluated and compared artificial intelligence methods on application, accuracy and the sensitivity of artificial intelligence in diagnosing and predicting diabetes (10 studies).
Conclusion: A systematic review of articles revealed that the use of data mining methods for diabetes management in Iran has been associated with good progress, but there is a need to design artificial intelligence systems and algorithms and more measures should be taken in the area of diabetes control and management.
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