Artificial Intelligence Applications in Type 2 Diabetes Mellitus Care: Focus on Machine Learning Methods

Healthcare Informatics Research
Shahabeddin AbhariAli Garavand


The incidence of type 2 diabetes mellitus has increased significantly in recent years. With the development of artificial intelligence applications in healthcare, they are used for diagnosis, therapeutic decision making, and outcome prediction, especially in type 2 diabetes mellitus. This study aimed to identify the artificial intelligence (AI) applications for type 2 diabetes mellitus care. This is a review conducted in 2018. We searched the PubMed, Web of Science, and Embase scientific databases, based on a combination of related mesh terms. The article selection process was based on Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Finally, 31 articles were selected after inclusion and exclusion criteria were applied. Data gathering was done by using a data extraction form. Data were summarized and reported based on the study objectives. The main applications of AI for type 2 diabetes mellitus care were screening and diagnosis in different stages. Among all of the reviewed AI methods, machine learning methods with 71% (n = 22) were the most commonly applied techniques. Many applications were in multi method forms (23%). Among the machine learning algorithms applications, support vector machine (21%...Continue Reading


Mar 12, 1987·The New England Journal of Medicine·W B SchwartzP Szolovits
Feb 5, 1999·IEEE Transactions on Bio-medical Engineering·R S ParkerN A Peppas
Jan 26, 2000·Critical Care Nursing Quarterly·L Quinn
Aug 31, 2004·Annals of the Royal College of Surgeons of England·A N RameshP J Drew
Sep 5, 2008·Diabetes Research and Clinical Practice·Mariam NaqshbandiFred Antwi-Nsiah
Sep 16, 2008·Artificial Intelligence in Medicine·Vimla L PatelAmeen Abu-Hanna
Oct 31, 2008·Briefings in Bioinformatics·Mohamed Radhouene AnibaJulie Dawn Thompson
Mar 14, 2009·Life Sciences·Christian K Roberts, Kunal K Sindhu
Oct 7, 2009·Journal of Hepato-biliary-pancreatic Sciences·José OberholzerEnrico Benedetti
Feb 23, 2010·Diabetes Research and Clinical Practice·Ping ZhangGregory Nichols
Nov 15, 2011·Diabetes Research and Clinical Practice·David R WhitingJonathan Shaw
Oct 16, 2012·Analytica Chimica Acta·Sandeep Kumar Vashist
Jan 22, 2013·Translational Research : the Journal of Laboratory and Clinical Medicine·Afsaneh MortezaAlireza Esteghamati
Dec 21, 2013·Diabetes Care·American Diabetes Association
Mar 13, 2014·IEEE Journal of Biomedical and Health Informatics·Bum Ju LeeJong Yeol Kim
Oct 16, 2014·Journal of Diabetes Science and Technology·Bharath SudharsanMansur Shomali
Feb 13, 2015·IEEE Journal of Biomedical and Health Informatics·Bum Ju Lee, Jong Yeol Kim
Aug 8, 2015·Journal of Innovation in Health Informatics·Ann R R RobertsonAziz Sheikh
Oct 18, 2015·Computer Methods and Programs in Biomedicine·Yi-Fan ZhangJing-Song Li
Dec 25, 2015·Computer Methods and Programs in Biomedicine·Hsiao-Hsien RauMing-Huei Hsu
May 14, 2016·Journal of the American Medical Informatics Association : JAMIA·Vibhu AgarwalNigam H Shah
Jun 9, 2016·Computers in Biology and Medicine·Herbert F JelinekSitalakshmi Venkatraman
Sep 13, 2016·Nursing Children and Young People
Sep 25, 2016·Soins. Gérontologie·Éric EttoreFrédéric Prate
Dec 7, 2016·International Journal of Medical Informatics·Tao ZhengYou Chen
Dec 10, 2016·Journal of Diabetes Science and Technology·Rina KagawaKazuhiko Ohe
Jan 28, 2017·Metabolism: Clinical and Experimental·Pavel Hamet, Johanne Tremblay
Feb 1, 2017·Computational and Structural Biotechnology Journal·Ioannis KavakiotisIoanna Chouvarda
Feb 6, 2017·Journal of Computer-aided Molecular Design·Jie CaiJun Xu
May 13, 2017·Journal of Diabetes Science and Technology·Arianna DagliatiRiccardo Bellazzi
May 26, 2017·Journal of Diabetes Science and Technology·Mercedes RiglaMaria Elena Hernando
Nov 29, 2017·Healthcare Informatics Research·Mina Fallah, Sharareh R Niakan Kalhori
Jun 1, 2018·Journal of Medical Internet Research·Ivan Contreras, Josep Vehi
Jul 6, 2018·Journal of Medical Internet Research·Kathrin CresswellAziz Sheikh


Apr 3, 2020·Journal of Occupational Rehabilitation·Andy S K ChengS W Law

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Blood Glucose
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