NCT07344792

Physician Diagnosis of Neurologic Cases With Large Language Models

Physician Diagnosis of Neurologic Cases Assisted by Large Language Models: A Randomized Controlled Trial

• Status: Completed
• Phase: N/A
• Study type: Interventional
• Enrollment: 40 (actual)
• Sponsor: Capital Medical University · Academic / Other
• Sex: All
• Age: —
• Healthy volunteers: Accepted

Summary

This study is a prospective randomized controlled trial that aims to evaluate whether large language model (LLM) assistance improves physicians' diagnostic performance compared with conventional assistance.

Detailed description

The study population consists of licensed physicians who have completed at least two years of neurology training. Participants are randomly assigned in a 1:1 ratio to the LLM assistance group or the conventional assistance group. In the LLM assistance group, physicians are assisted by an in-house LLM and are allowed to use conventional resources (e.g., search engines, UpToDate, or clinical guidelines) before submitting a final diagnosis. Access to any other LLMs is not permitted. In the conventional assistance group, physicians use only conventional resources and do not have access to the in-house LLM or any other LLMs at any point during the study. The primary outcome is top-1 diagnostic accuracy. Secondary outcomes include top-3 diagnostic accuracy, the time required to complete each case, and physicians' diagnostic confidence.

Conditions

• Neurology

Interventions

Type	Name	Description
OTHER	LLM assistance	Physicians are assisted by an in-house large language model and are allowed to use conventional resources. Access to any other LLMs is not permitted.

Timeline

• Start date: 2026-01-17
• Primary completion: 2026-01-28
• Completion: 2026-01-28
• First posted: 2026-01-15
• Last updated: 2026-01-29

Locations

3 sites across 1 country: China