인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
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논문을 무제한 열람 이용할 수 있어요.
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
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연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
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DBpia Top 5%동일한 주제분류 기준으로최근 2년간 이용수 순으로 정렬했을 때
해당 논문이 위치하는 상위 비율을 의미합니다.
초록· 키워드
Objectives: We aimed to explore the use of generative AI, specifically ChatGPT, in clinical practice education for Korean Medicine (KM) students. We focused on enhancing their ability to provide personalized lifestyle guidance and analog-type symptom-tracking tools for managing chronic non-communicable diseases (NCDs).
Methods: The class was part of a clinical practice course for third-year KM students. The course included role-playing and PBL combined with CBL in four modules: cardiology and neurology I, cardiology and neurology II, gynecology, and acupuncture and moxibustion medicine. In each session, students used ChatGPT 4o to create tailored patient educational materials and symptom diaries based on patient case scenarios. These results were shared and discussed throughout the presentations. After completing all modules, students took a survey to assess their satisfaction with ChatGPT and its potential for future applications.
Results: Students effectively used ChatGPT in all four modules to provide individualized lifestyle advice and symptom records, tailoring the outputs to suit patient needs. When ChatGPT became momentarily unavailable, Claude was utilized as a replacement. Student feedback indicated that generative AI could enhance their understanding of disease-specific lifestyle management and improve their efficiency in creating patient-centered educational materials.
Conclusions: Integrating generative AI into clinical education allows KM students to gain real experience in tailored healthcare delivery. As generative artificial intelligence becomes more extensively employed, various Korean medical college education programs utilizing it should be implemented in the future.
Methods: The class was part of a clinical practice course for third-year KM students. The course included role-playing and PBL combined with CBL in four modules: cardiology and neurology I, cardiology and neurology II, gynecology, and acupuncture and moxibustion medicine. In each session, students used ChatGPT 4o to create tailored patient educational materials and symptom diaries based on patient case scenarios. These results were shared and discussed throughout the presentations. After completing all modules, students took a survey to assess their satisfaction with ChatGPT and its potential for future applications.
Results: Students effectively used ChatGPT in all four modules to provide individualized lifestyle advice and symptom records, tailoring the outputs to suit patient needs. When ChatGPT became momentarily unavailable, Claude was utilized as a replacement. Student feedback indicated that generative AI could enhance their understanding of disease-specific lifestyle management and improve their efficiency in creating patient-centered educational materials.
Conclusions: Integrating generative AI into clinical education allows KM students to gain real experience in tailored healthcare delivery. As generative artificial intelligence becomes more extensively employed, various Korean medical college education programs utilizing it should be implemented in the future.
#Medical education
#Korean medicine
#Problem-based learning
#Generative artificial intelligence
#ChatGPT
#Personalized medicine
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