Accepted for/Published in: JMIR Medical Education
Date Submitted: Sep 5, 2023
Date Accepted: Jan 17, 2024
Embracing ChatGPT for Medical Education: Exploring its Impact on Doctors and Medical Students
ABSTRACT
ChatGPT, a cutting-edge natural language processing model, holds immense promise for revolutionizing medical education. With its remarkable performance in language-related tasks, ChatGPT offers personalized and efficient learning experiences for medical students and doctors. Through training, it enhances clinical reasoning and decision-making skills, leading to improved case analysis and diagnosis. The model facilitates simulated dialogues, intelligent tutoring, and automated question answering, enabling practical application of medical knowledge. However, integrating ChatGPT in medical education raises ethical and legal concerns. Safeguarding patient data and adhering to data protection regulations are critical. Transparent communication with students, physicians, and patients is essential to ensure their understanding of the technology’s purpose and implications, as well as potential risks and benefits. Maintaining a balance between personalized learning and face-to-face interactions is crucial to avoid hindering critical thinking and communication skills. Despite challenges, ChatGPT offers transformative opportunities. Integrating it with Problem-Based Learning, Team-Based Learning, and Case-Based Learning methodologies can further enhance medical education. With proper regulation and supervision, ChatGPT can contribute to a well-rounded learning environment, nurturing skilled and knowledgeable medical professionals ready to tackle healthcare challenges. By emphasizing ethical considerations and human-centric approaches, ChatGPT’s potential can be fully harnessed in medical education, benefiting both students and patients alike.
Citation
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Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.