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

Abstract

Authors

• Malede Berihun Yismaw
  Department of Pharmacy, College of Medicine and Health Sciences, Bahr Dar University, Bahr Dar, Ethiopia. Electronic address: malepharm@gmai.com.
• Chernet Tafere
  Department of Pharmacy, College of Medicine and Health Sciences, Bahr Dar University, Bahr Dar, Ethiopia.
• Bereket Bahiru Tefera
  Department of Pharmacy, College of Medicine and Health Sciences, Bahr Dar University, Bahr Dar, Ethiopia.
• Desalegn Getnet Demsie
  Department of Pharmacy, College of Medicine and Health Sciences, Bahr Dar University, Bahr Dar, Ethiopia.
• Kebede Feyisa
  Department of Pharmacy, College of Medicine and Health Sciences, Bahr Dar University, Bahr Dar, Ethiopia.
• Zenaw Debasu Addisu
  Department of Pharmacy, College of Medicine and Health Sciences, Bahr Dar University, Bahr Dar, Ethiopia.
• Tirsit Ketsela Zeleke
  Department of Pharmacy, College of Health Sciences, Debre Markos University, Debre Markos, Ethiopia.
• Ebrahim Abdela Siraj
  Department of Pharmacy, College of Medicine and Health Sciences, Bahr Dar University, Bahr Dar, Ethiopia.
• Minichil Chanie Worku
  Department of Pharmaceutical Chemistry, School of Pharmacy, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia.
• Fasikaw Berihun
  School of Medicine, College of Medicine and Health Sciences, Bahr Dar University, Bahr Dar, Ethiopia.

Keywords

External Resources