Teaching AI to doctors: a new way to build trust?

NCT ID NCT07743658

Completed Knowledge-focused Sponsor: University of Liberia Source: ClinicalTrials.gov ↗

First seen Aug 04, 2026 · Last updated Aug 05, 2026 · Updated 1 time

Summary

This trial tests whether teaching medical students with explainable AI (XAI) tools improves their understanding and trust in AI compared to traditional lectures. Third-year medical students will use an interactive module that explains AI decisions in brain imaging, then complete assessments. The goal is to see if this approach reduces cognitive workload and boosts AI literacy.

What this could mean

Our plain-language read of the trial. This is informational only — not medical advice or a prediction.

Active substance: XAI-Enhanced Interactive Module (CerViD-MultiModal) with SHAP and LIME explanations
What this could lead to: If effective, this approach could reshape how medical students learn to work with AI, fostering better human-AI collaboration in diagnostics.
What could go wrong: This is a small, single-center study with 120 students, so results may not generalize. The intervention is educational, so benefits may be limited to learning outcomes rather than direct patient care.

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Conditions

The condition(s) this trial relates to.

Cognitive Dysfunction

As listed by the trial registrant

The condition terms exactly as the trial's registrant entered them.

MEDICAL EDUCATION

Contacts and locations

Locations

University of Liberia Medical School

Monrovia, Montserrado County, 1000, Liberia

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