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Currently submitted to: JMIR Medical Education

Date Submitted: Jun 7, 2026
Open Peer Review Period: Jun 9, 2026 - Aug 4, 2026
(currently open for review)

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

Research on AI Powered Problem-based Learning in Organ-System-Based Curriculum of Medicine Education

  • Renyuan Li; 
  • Xinyue Cheng; 
  • Cuiting Liu; 
  • Ying Zhang; 
  • Ze Li; 
  • Feng Zhang

ABSTRACT

Background:

A new manner integrating AI with Problem-Based Learning (PBL) in an Organ-System-Based Curriculum (OSC) could be a promising pathway to strengthen medical students’ comprehensive abilities.

Objective:

Integrating AI with Problem Based Learning (PBL) within an Organ System Based Curriculum (OSC) may strengthen medical students’ comprehensive abilities. This study aimed to develop and evaluate an AI Powered PBL model in OSC.

Methods:

Integrating AI with Problem Based Learning (PBL) within an Organ System Based Curriculum (OSC) may strengthen medical students’ comprehensive abilities. This study aimed to develop and evaluate an AI Powered PBL model in OSC.

Results:

Integrating AI with Problem Based Learning (PBL) within an Organ System Based Curriculum (OSC) may strengthen medical students’ comprehensive abilities. This study aimed to develop and evaluate an AI Powered PBL model in OSC.

Conclusions:

Integrating AI with Problem Based Learning (PBL) within an Organ System Based Curriculum (OSC) may strengthen medical students’ comprehensive abilities. This study aimed to develop and evaluate an AI Powered PBL model in OSC.


 Citation

Please cite as:

Li R, Cheng X, Liu C, Zhang Y, Li Z, Zhang F

Research on AI Powered Problem-based Learning in Organ-System-Based Curriculum of Medicine Education

JMIR Preprints. 07/06/2026:103913

DOI: 10.2196/preprints.103913

URL: https://preprints.jmir.org/preprint/103913

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