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AI-Assisted Learning in Medicine

NCT06945159 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 1632

Last updated 2025-04-25

No results posted yet for this study

Summary

This multi-center retrospective cohort study investigates the real-world impact of integrating MetaGP-Edu, a proprietary AI tool fine-tuned for medical education, into the undergraduate Internal Medicine curriculum. Utilizing historical academic records from several major medical institutions in China across multiple academic years, the study compares the performance of student cohorts who learned via traditional methods only with subsequent cohorts who had supplementary access to MetaGP-Edu. The primary outcome measure is overall academic performance in the Internal Medicine course, assessed through final course scores. The analysis aims to determine if access to the AI tool as a supplementary resource is associated with differences in learning outcomes, while statistically accounting for baseline student characteristics and other potential confounders between the compared cohorts.

Conditions

  • Medical Student

Sponsors & Collaborators

  • Kang Zhang

    lead OTHER

Eligibility

Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2020-06-01
Primary Completion
2024-12-01
Completion
2024-12-01

Countries

  • China

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06945159 on ClinicalTrials.gov