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Trial Title The Impact of Large Language Models on Diagnostic Reasoning Among Medical Doctors Diagnostic Reasoning With and Without AI Support: A Randomized Controlled Trial of LLM-Trained Medical Doctors
Abstract Diagnostic errors are a major source of preventable patient harm. Large language models (LLMs) have shown promise in assisting with clinical decision-making, potentially improving diagnostic accuracy and efficiency. However, the impact of LLMs on medical doctors' diagnostic reasoning compared to conventional diagnostic resources remains unclear. This study aims to evaluate whether providing medical doctors (including physicians and surgeons) with access to ChatGPT-4o, in addition to standard resources, enhances their diagnostic reasoning performance. All participating doctors will have completed at least a 10-hour training program covering ChatGPT-4o usage, prompt engineering techniques, and output evaluation strategies. Diagnostic errors are a major source of preventable patient harm. Large language models (LLMs) have shown promise in assisting with clinical decision-making, potentially improving diagnostic accuracy and efficiency. However, the impact of LLMs on medical doctors' diagnostic reasoning compared to conventional diagnostic resources remains unclear. This study aims to evaluate whether providing LLM-trained medical doctors (including physicians and surgeons) with access to ChatGPT-4o, in addition to standard resources, enhances their diagnostic reasoning performance. All participating doctors will have completed at least a 10-hour training program covering ChatGPT-4o usage, prompt engineering techniques, and output evaluation strategies.
Last Published January 18, 2025 01:24 PM March 17, 2025 01:54 AM
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