Quick training boosts AI doctor accuracy in simulation trial

NCT ID NCT07651280

First seen Jun 27, 2026 · Last updated Jun 27, 2026

Summary

This study tests whether a short, three-minute education session can help people get better medical advice from AI tools like ChatGPT and Gemini. About 525 healthy adults will simulate asking about health problems, with some receiving the training first. The goal is to see if the training improves how well the AI identifies possible conditions and recommends the right level of care.

What this could mean

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

Active substance

three-minute six-dimensions education (3M-6D education)

What this could lead to

If successful, this could show that a short training session helps people get more accurate medical information from AI assistants, potentially improving how the public uses these tools.

What could go wrong

This is a small, early simulation study, not a real-world test. Results may not apply to actual medical situations, and AI advice can still be wrong or harmful.

Disclaimer Read more

This is a summary of the original study . Summaries may miss details or leave out important information. Before applying or accepting participation, make sure you have read and understood the full study. Curemydisease.com takes no responsibility whatsoever for anything missed, misunderstood, or acted upon as a result of our summary — we know it does not capture everything.

Get updates

Get notified about this study

Sign up to get updates when this study changes or when new studies for RELEVANT CONDITIONS IDENTIFICATION are added.

Our safety recommendation!

By submitting, you agree to our Terms of use

As listed by the trial registrant

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

Contacts and locations

Study contacts

  • Contact

    Phone: •••-•••-•••• Email: •••••@•••••

  • Contact

    Phone: •••-•••-•••• Email: •••••@•••••

Locations

  • Xuanwu Hospital, Capital Medical University

    Beijing, Beijing Municipality, 100053, China

    Contact Phone: •••-•••-•••• Email: •••••@•••••