2026· Complementary Medicine Education and Research· Vol 3· 0 citations
TL;DR
The application and educational impact of AI across major domains of TCM clinical education, including visual inspection, auscultation and olfaction, inquiry, pulse palpation, clinical case writing, the study of TCM classics and master physician apprenticeship, clinical reasoning, scientific research innovation, and interdisciplinary integration are reviewed.
Abstract
Artificial intelligence (AI) is increasingly transforming medical education and provides new opportunities for the reform and development of traditional Chinese medicine (TCM) clinical teaching. This article reviews the application and educational impact of AI across major domains of TCM clinical education, including visual inspection, auscultation and olfaction, inquiry, pulse palpation, clinical case writing, the study of TCM classics and master physician apprenticeship, clinical reasoning, scientific research innovation, and interdisciplinary integration. AI can enrich teaching resources, facilitate the visualisation and simulation of clinical processes, support case analysis and clinical reasoning, improve learning efficiency, and promote interdisciplinary integration and educational innovation. However, its application also presents challenges, including limitations and inaccuracies in professional knowledge, potential over-reliance on AI that may weaken students’ practical and independent clinical skills, and risks to academic integrity and medical ethics. Therefore, AI should be regarded as a complementary educational tool rather than a substitute for clinical expertise. Medical students should independently acquire comprehensive and in-depth theoretical knowledge through self-directed learning and critical thinking, while developing clinical experience and practical wisdom through supervised clinical practice. The responsible integration of AI into TCM clinical education requires critical evaluation of AI-generated information, appropriate teacher supervision, and continued emphasis on academic integrity, medical ethics, and the preservation of essential human-centred clinical competencies.
AI delivers its greatest value when deployed as a collaborative instrument that augments rather than replaces clinical judgment, which depends on sustained investment in digital literacy, explainable systems, clinician involvement in design, and equitable institutional infrastructure.
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Doctor-patient communication is an essential core professional competency for physicians and a key training component for medical students during clinical internships. Currently, the teaching of doctor-patient communication in clinical internships across China is generally plagued by rigid teaching models, insufficient...
Objective: To explore medical students' perceptions, attitudes, current status, and development prospects regarding artificial intelligence (AI)-enhanced clinical skills teaching, and to provide empirical evidence for optimizing the application of AI in clinical skills education.
Methods: A questionnaire survey was con...
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Modern generative artificial intelligence technologies are fundamentally reshaping the pedagogical paradigm of evidence-based medicine (EBM). This article systematically articulates the mechanisms by which AI augments EBM instruction—encompassing large language models, knowledge graphs, and rule engines—with a specific...
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This review aimed to explore possible applications of various technologies based on AI principles for fostering clinical
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patients, and AI-supported assessments. The literature review was perform...
Saman Tauqir, H. Faisal, Saif Ullah Shaikh et al.· Journal of Bahria University...· 0 citations
This review aims to present how AI tools are currently used across the medical education continuum, what problems they create and where the field may be heading.
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