Integrating Generative AI into Clinical Practice Education: Enhancing Personalized Medicine Delivery Skills for Korean Medicine Students

Miso S. Park; Ju Hyun Jeon; Junyoung Hur; Horyong Yoo; Ji-Yeon Lee; Park, Miso S.; Jeon, Ju Hyun; Hur, Junyoung; Yoo, Horyong; Lee, Ji-Yeon

doi:10.13048/jkm.25007

JKM > Volume 46(1); 2025 > Article

Park, Jeon, Hur, Yoo, and Lee: Integrating Generative AI into Clinical Practice Education: Enhancing Personalized Medicine Delivery Skills for Korean Medicine Students

Original Article

The Journal of Korean Medicine 2025; 46(1): 87-102.

Published online: March 01, 2025

DOI: https://doi.org/10.13048/jkm.25007

Integrating Generative AI into Clinical Practice Education: Enhancing Personalized Medicine Delivery Skills for Korean Medicine Students

Miso S. Park¹

, Ju Hyun Jeon²

, Junyoung Hur¹

, Horyong Yoo¹

, Ji-Yeon Lee³^{, *}

¹Department of Cardiology and Neurology of Korean Medicine, College of Korean Medicine, Daejeon University

²Department of Acupuncture and Moxibustion Medicine, College of Korean Medicine, Daejeon University

³Department of Obstetrics and Gynecology of Korean Medicine, College of Korean Medicine, Daejeon University

Correspondence to: Ji-Yeon Lee, Daejeon Korean Medicine Hospital of Daejeon University, 75 Daeduk-daero 176 beon-gil, Seo-gu, Daejeon, Tel: +82-42-470-9139, Fax: +82-42-470-9009, E-mail: jyounl@daum.net

Received January 21, 2025 Revised February 18, 2025 Accepted February 21, 2025

Abstract

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.

Keywords: Medical education, Korean medicine, Problem-based learning, Generative artificial intelligence, ChatGPT, Personalized medicine

Supplementary materials

jkm-46-1-87-Supplementary-1.pdf

Fig. 1

Example of lifestyle education message generated using ChatGPT

Fig. 2

Example of a daily log generated using ChatGPT

Fig. 3

An example of a lifestyle education message and daily log using ChatGPT created in module 1 (cardiology and neurology 1).

Fig. 4

An example of a lifestyle education message and daily log using ChatGPT created in module 2 (gynecology).

Fig. 5

An example of a lifestyle education message using ChatGPT created in module 3 (acupuncture and moxibustion medicine).

Fig. 6

An example of a lifestyle education message and daily log using Claude created in module 1 (cardiology and neurology 2).

Fig. 7

Draft questionnaire created using ChatGPT.

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