Harnessing ChatGPT for Medical Education: A Narrative Review.

Area of Science:

• Medical Education Technology
• Artificial Intelligence in Healthcare
• Large Language Models (LLMs)

Background:

• Artificial intelligence (AI), particularly large language models (LLMs) like ChatGPT, is increasingly impacting various sectors, including medical education.
• Innovative, learner-centered approaches are being introduced through generative AI tools, showing potential in teaching, learning, assessment, and curriculum design.

Purpose of the Study:

• To provide a comprehensive overview of the applications, benefits, and limitations of ChatGPT in medical education.
• To analyze the role of AI and LLMs in enhancing medical training and educational efficiency.

Main Methods:

• A narrative review approach was employed.
• Literature search conducted in PubMed and Google Scholar for studies up to 2025 focusing on ChatGPT, AI, and medical education.
• Qualitative synthesis of relevant peer-reviewed articles, including original studies and reviews.

Main Results:

• ChatGPT aids educators in generating teaching materials, curriculum development, and assessment/feedback.
• For learners, it acts as a virtual tutor, promoting self-directed learning via interactive explanations, simulations, and self-assessment.
• Personalized, real-time, and multilingual support enhances accessibility, especially in diverse and resource-constrained settings like India.

Conclusions:

• ChatGPT is a promising adjunct for medical education, improving learning experiences and efficiency.
• Limitations include potential inaccuracies, bias, academic integrity concerns, data privacy, and over-reliance impacting critical thinking.
• Effective integration requires oversight, ethical considerations, and active educator involvement for safe and effective use.