AccScience Publishing / AIH / Online First / DOI: 10.36922/AIH025410088
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MINI-REVIEW

Artificial intelligence in health sciences education: A mini-review of clinical reasoning development and educator perceptions

Nadia Hachoumi1* ,  Mohamed Eddabbah2 ,  Ahmed Rhassane El Adib1,3,4
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1 Department of Biosciences and Health, Faculty of Medicine and Pharmacy of Marrakesh, Cadi Ayyad University, Marrakesh, Morocco
2 LaRTID Laboratory, Higher School of Technology of Essaouira, Cadi Ayyad University (UCA), Marrakesh, Morocco
3 Simulation and Innovation in Health Sciences Center, Faculty of Medicine and Pharmacy of Marrakesh, Cadi Ayyad University, Marrakesh, Morocco
4 Mohammed VI University of Sciences and Health, Casablanca, Morocco
AIH, 025410088 https://doi.org/10.36922/AIH025410088
Received: 10 October 2025 | Revised: 13 November 2025 | Accepted: 21 November 2025 | Published online: 5 December 2025
© 2025 by the Author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution 4.0 International License ( https://creativecommons.org/licenses/by/4.0/ )
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Abstract

Clinical reasoning forms the basis of practice in the health sciences, enabling professionals to collect and interpret patient data to support sound clinical decisions. Artificial intelligence (AI) and machine learning (ML) have emerged as strong tools, revolutionizing diagnosis, personalizing treatment, and enhancing therapeutic outcomes. However, very little research has been conducted concerning health sciences educators’ perceptions regarding AI and its role in clinical reasoning skill development. This mini-review examines AI’s growing prevalence in health sciences education, as well as the challenges and opportunities it presents. A systematic search of the scholarly literature identified studies related to AI applications in the teaching and learning of clinical reasoning. A number of recurring themes emerged from these analyses, including the potential for AI to transform the training of clinical skills, the ethical implications associated with AI implementation, contributions from the field of ML to clinical data analysis, and innovations in educational assessment. Thus, these findings highlight the need for ethical frameworks, interdisciplinary collaborations, and sustained research to enhance the benefits of AI. Proper integration of AI in health sciences education would significantly assist students in improving their clinical reasoning skills, enabling them to become competent practitioners so that, ultimately, patients may benefit in an increasingly digital health environment.

Graphical abstract
Keywords
Clinical reasoning
Artificial intelligence
Machine learning
Health sciences education
Personalized learning
Funding
None.
Conflict of interest
The authors declare that they have no competing interests.
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Artificial Intelligence in Health, Electronic ISSN: 3029-2387 Print ISSN: 3041-0894, Published by AccScience Publishing
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