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This article introduces ClinicalGPT-R1, a large language model specifically optimized for clinical reasoning and disease diagnosis using 20,000 real-world records. The study benchmarks the model against GPT-4o and GPT-4, demonstrating superior performance in Chinese diagnostic tasks while maintaining competitive results in English settings. This research advances the application of LLMs beyond coding and math into critical medical domains, offering a new tool for generalist disease diagnosis.
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ClinicalGPT-R1: Pushing reasoning capability of generalist disease diagnosis with large language model

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arXiv:2504.09421v3 Announce Type: replace-cross Abstract: Recent advances in reasoning with large language models (LLMs)has shown remarkable reasoning capabilities in domains such as mathematics and coding, yet their application to clinical diagnosis remains underexplored. Here, we introduce ClinicalGPT-R1, a reasoning enhanced generalist large language model for disease diagnosis. Trained on a dataset of 20,000 real-world clinical records, ClinicalGPT-R1 leverages diverse training strategies to enhance diagnostic reasoning. To benchmark performance, we curated MedBench-Hard, a challenging dataset spanning seven major medical specialties and representative diseases. Experimental results demonstrate that ClinicalGPT-R1 outperforms GPT-4o in Chinese diagnostic tasks and achieves comparable performance to GPT-4 in English settings. This comparative study effectively validates the superior performance of ClinicalGPT-R1 in disease diagnosis tasks. Resources are available at https://github.com/medfound/medfound.

Abstract:Recent advances in reasoning with large language models (LLMs)has shown remarkable reasoning capabilities in domains such as mathematics and coding, yet their application to clinical diagnosis remains underexplored. Here, we introduce ClinicalGPT-R1, a reasoning enhanced generalist large language model for disease diagnosis. Trained on a dataset of 20,000 real-world clinical records, ClinicalGPT-R1 leverages diverse training strategies to enhance diagnostic reasoning. To benchmark performance, we curated MedBench-Hard, a challenging dataset spanning seven major medical specialties and representative diseases. Experimental results demonstrate that ClinicalGPT-R1 outperforms GPT-4o in Chinese diagnostic tasks and achieves comparable performance to GPT-4 in English settings. This comparative study effectively validates the superior performance of ClinicalGPT-R1 in disease diagnosis tasks. Resources are available at this https URL.

Computation and Language (cs.CL); Artificial Intelligence (cs.AI)

arXiv:2504.09421 [cs.CL]

(or arXiv:2504.09421v3 [cs.CL] for this version)

https://doi.org/10.48550/arXiv.2504.09421 Focus to learn more arXiv-issued DOI via DataCite

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