Machine learning applications to classify and monitor medication adherence in patients with type 2 diabetes in Ethiopia

This study highlights a variety of machine learning (ML) models that can be effectively used to monitor and classify medication adherence in diabetic patients in Ethiopia. However, to fully realize the potential impact of digital health applications, further studies that include patients from diverse settings are necessary. Such research could enhance the generalizability of these models and provide insights into the broader applicability of digital tools for improving medication adherence and patient outcomes in varying healthcare contexts.

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Publication Details

Journal
Frontiers in Endocrinology
Published
2025-03-20
DOI
https://doi.org/10.3389/fendo.2025.1486350
Citations
2
Primary Topic
Medication Adherence and Compliance
Type
article
Field-Weighted Citation Impact
3.03
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article

Machine learning applications to classify and monitor medication adherence in patients with type 2 diabetes in Ethiopia

Biruk Beletew Abate, Bekele Mulat Enyew, Ashenafi Kibret Sendekie, Ewunate Assaye Kassaw
2 citations
Frontiers in Endocrinology
Medication Adherence and Compliance
3.03
article

Machine learning applications to classify and monitor medication adherence in patients with type 2 diabetes in Ethiopia

Biruk Beletew Abate, Bekele Mulat Enyew, Ashenafi Kibret Sendekie, Ewunate Assaye Kassaw
article en
2 citations

Abstract

This study highlights a variety of machine learning (ML) models that can be effectively used to monitor and classify medication adherence in diabetic patients in Ethiopia. However, to fully realize the potential impact of digital health applications, further studies that include patients from diverse settings are necessary. Such research could enhance the generalizability of these models and provide insights into the broader applicability of digital tools for improving medication adherence and patient outcomes in varying healthcare contexts.

Frontiers in EndocrinologyVol. 16
Curtin University (AU), Woldia University (ET), Indian Institute of Technology Delhi (IN), University of Gondar (ET)
Openalex Percentile: Top 9%
Medication Adherence and Compliance
3.03
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Machine learning applications to classify and monitor medication adherence in patients with type 2 diabetes in Ethiopia — Biruk Beletew Abate, Bekele Mulat Enyew, et al. · Frontiers in Endocrinology (2025) | TGRS Research Map | TGRS