Artificial intelligence based predictive tools for identifying type 2 diabetes patients at high risk of treatment Non-adherence: A systematic review.

Saved in:
Bibliographic Details
Title: Artificial intelligence based predictive tools for identifying type 2 diabetes patients at high risk of treatment Non-adherence: A systematic review.
Authors: Yismaw MB; Department of Pharmacy, College of Medicine and Health Sciences, Bahr Dar University, Bahr Dar, Ethiopia. Electronic address: malepharm@gmai.com., Tafere C; Department of Pharmacy, College of Medicine and Health Sciences, Bahr Dar University, Bahr Dar, Ethiopia., Tefera BB; Department of Pharmacy, College of Medicine and Health Sciences, Bahr Dar University, Bahr Dar, Ethiopia., Demsie DG; Department of Pharmacy, College of Medicine and Health Sciences, Bahr Dar University, Bahr Dar, Ethiopia., Feyisa K; Department of Pharmacy, College of Medicine and Health Sciences, Bahr Dar University, Bahr Dar, Ethiopia., Addisu ZD; Department of Pharmacy, College of Medicine and Health Sciences, Bahr Dar University, Bahr Dar, Ethiopia., Zeleke TK; Department of Pharmacy, College of Health Sciences, Debre Markos University, Debre Markos, Ethiopia., Siraj EA; Department of Pharmacy, College of Medicine and Health Sciences, Bahr Dar University, Bahr Dar, Ethiopia., Worku MC; Department of Pharmaceutical Chemistry, School of Pharmacy, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia., Berihun F; School of Medicine, College of Medicine and Health Sciences, Bahr Dar University, Bahr Dar, Ethiopia.
Source: International journal of medical informatics [Int J Med Inform] 2025 Jun; Vol. 198, pp. 105858. Date of Electronic Publication: 2025 Mar 01.
Publication Type: Journal Article; Systematic Review
Journal Info: Publisher: Elsevier Science Ireland Ltd Country of Publication: Ireland NLM ID: 9711057 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1872-8243 (Electronic) Linking ISSN: 13865056 NLM ISO Abbreviation: Int J Med Inform Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1872-8243
DOI:10.1016/j.ijmedinf.2025.105858