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CODE MEDI: A Collaborative Hackathon for Health Informatics Education
Hyeon Ji Kim1, Sona Ha1, Jaerang Go2
1Department of Data Sciences Convergence, Dong-A University, Republic of Korea.
Studies in Health Technology and Informatics
|May 23, 2026
Summary
The CODE MEDI hackathon successfully integrated medical and computer science students, fostering AI skills and mutual understanding. This interdisciplinary approach proved effective for medical AI education.
Area of Science:
- Medical Education
- Artificial Intelligence
- Software Engineering
Background:
- Medical education increasingly requires integration of artificial intelligence (AI) and software (SW) principles.
- Interdisciplinary collaboration between medical and computer science fields is crucial for developing healthcare innovations.
Purpose of the Study:
- To evaluate the CODE MEDI program, a two-day hackathon designed to promote interdisciplinary learning between medical and computer science students.
- To assess the effectiveness of a hackathon model for fostering AI and software skills in a medical context.
Main Methods:
- A two-day hackathon (CODE MEDI) involving 36 students (21 medical, 15 engineering/AI) in mixed teams.
- Development of healthcare-related prototype models.
- Post-event surveys and word-cloud analysis of open-ended feedback.
Main Results:
- High participant satisfaction (8.34 ± 1.75/10) and agreement on teamwork, mentoring, and interdisciplinary learning.
- Key collaboration challenge identified as differing technical terminology (46.8%).
- Frequent themes in feedback included knowledge, learning, medical, and experience.
Conclusions:
- The CODE MEDI program effectively fostered mutual understanding and practical AI application skills.
- Hackathon-based learning is a valuable model for integrating AI and software education into medical curricula.
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