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Artificial Intelligence in Improving Stroke Diagnosis: Focus on Machine Learning Models and Explainable AI Application Cover

Artificial Intelligence in Improving Stroke Diagnosis: Focus on Machine Learning Models and Explainable AI Application

EABR. Experimental and Applied Biomedical Research
Volume 26 (2025): Issue 4 (December 2025)
By: Natacha Usanase,  Consolée Uwamahoro and  Dilber Uzun Ozsahin  
Open Access
|Feb 2026

Authors

Natacha Usanase

natacha.usanase@neu.edu.tr

Operational Research Center in Healthcare, Near East University, Nicosia/TRNC, Turkey
Department of Biomedical Engineering, Near East University, Nicosia, Turkey

Consolée Uwamahoro

Department of Biomedical Laboratory Sciences, Faculty of Applied Fundamental Sciences, Ines-Ruhengeri, Rwanda

Dilber Uzun Ozsahin

Department of Medical Diagnostic Imaging, College of Health Science, University of Sharjah, Sharjah, UAE
Research Institute for Medical and Health Sciences, University of Sharjah, Sharjah, UAE
Operational Research Center in Healthcare, Near East University, Nicosia/TRNC, Turkey
DOI: https://doi.org/10.2478/eabr-2025-0023 | Journal eISSN: 2956-2090 | Journal ISSN: 2956-0454
Journal RSS Feed
Language: English
Page range: 391 - 397
Submitted on: Oct 7, 2025
|
Accepted on: Nov 12, 2025
|
Published on: Feb 25, 2026
Published by: University of Kragujevac, Faculty of Medical Sciences
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Keywords:
Stroke,
machine learning,
data analysis,
diagnosis,
prediction,
LIME
Related subjects:
Medicine,
Clinical medicine,
Clinical medicine, other

© 2026 Natacha Usanase, Consolée Uwamahoro, Dilber Uzun Ozsahin, published by University of Kragujevac, Faculty of Medical Sciences
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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