Explainable AI in Medical Education: CerViD-MultiModal Framework Trial

Completed · Not applicable

Conditions studied: Medical Education

In brief

This study evaluates whether Explainable Artificial Intelligence (XAI) explanations integrated into medical training improve AI literacy, reduce cognitive workload, and enhance learner trust compared to traditional lecture methods. Third-year medical students participated in a randomized controlled trial assessing the CerViD-MultiModal diagnostic framework during a neuroimaging diagnostic module focused on fornix atrophy in early and late mild cognitive impairment

Key facts

Study ID

NCT07743658

Run by

University of Liberia

People needed

120

Starts

2026-05-30

Expected to finish

2026-06-15

Last updated by the study team

2026-08-04

Who can join

Age: 18 and older. Sex: any. Healthy volunteers: accepted.

You may qualify if…

• Enrolled as a third-year medical student in the clinical neuroscience rotation at the University of Liberia.
• Willing and able to complete the 45-minute educational module and post-intervention evaluations.
• Provided informed consent to participate in the study.

You may not qualify if…

• Prior formal coursework, professional training, or specialized technical degree in artificial intelligence, machine learning, or computer science.
• Inability to complete the post-intervention assessment.

Where it is running

• University of Liberia Medical School — Monrovia, Montserrado County, Liberia

Full record on ClinicalTrials.gov

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