An interventional study of ChatGPT-4o in Diagnosis, sponsored by Lahore University of Management Sciences. Completed at 1 site in Pakistan. Per ClinicalTrials.gov, last updated 2025-07-17.
Sponsored by Lahore University of Management Sciences · Not applicable, Interventional, and Diagnostic
This study aims to evaluate whether large language model-trained medical doctors demonstrate enhanced diagnostic reasoning performance when utilizing ChatGPT-4o alongside conventional resources compared to using conventional resources alone.
Diagnostic errors are a major source of preventable patient harm. Recent advances in Large Language Models (LLM), particularly ChatGPT-4o, have shown promise in enhancing medical decision-making. However, little is known about their impact on medical doctors' (e.g., physicians' and surgeons') diagnostic reasoning.
Diagnostic accuracy relies on complex clinical reasoning and careful evaluation of patient data. While AI assistance could potentially reduce errors and improve efficiency, ChatGPT-4o lacks medical validation and could introduce new risks through incorrect information generation (also known as hallucinations). To mitigate these risks, doctors need adequate training in understanding ChatGPT-4o's capabilities, limitations, and proper usage. Given these uncertainties and the importance of proper AI training, systematic evaluation is essential before clinical implementation.
This randomized study will assess whether ChatGPT-4o access improves LLM-trained medical doctors' diagnostic performance compared to conventional resources (e.g., textbooks, online medical databases) alone. All participating doctors will have completed at least a 10-hour training program covering ChatGPT-4o usage, prompt engineering techniques, and output evaluation strategies. Participants will provide differential diagnoses with supporting evidence and recommended next steps for clinical cases, with responses evaluated by blinded reviewers.
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This study's enrollment of 60 is below the median of 80 across 732 interventional studies indexed under Disease.
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Exclusion Criteria:
Group will be given access to ChatGPT-4o.
Other: ChatGPT-4o
Group will not be given access to ChatGPT-4o but will be encouraged to use any resources they wish besides large language models (PubMed, Google without AI Overviews, etc).
OpenAI's ChatGPT-4o large language model with chat interface.
Diagnostic reasoning
The primary outcome will be the percent correct for each case (range: 0 to 100). For each case, participants will be asked for three top diagnoses, findings from the case that support that diagnosis, and findings from the case that oppose that diagnosis. For each plausible diagnosis, participants will receive 1 point. Findings supporting the diagnosis and findings opposing the diagnosis will also be graded based on correctness, with 1 point for partially correct and 2 points for completely correct responses. Participants will then be asked to name their top diagnosis, earning one point for a reasonable response and two points for the most correct response. Finally participants will be asked to name up to 3 next steps to further evaluate the patient with one point awarded for a partially correct response and two points for a completely correct response. The primary outcome will be compared on the case-level by the randomized groups.
Time frame: Assessed at a single time point for each case, during the scheduled diagnostic reasoning evaluation session, which takes place between 0-4 days after participant enrollment.
Time Spent on Diagnosis
We will compare how much time (in seconds) participants spend per case between the two study arms.
Time frame: Assessed at a single time point for each case, during the scheduled diagnostic reasoning evaluation session, which takes place between 0-4 days after participant enrollment.
Plan to share: No
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This study is completed, as verified in Jul 2025. You cannot join it, but the record below documents what was studied.
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Lahore University of Management Sciences