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AgentMD: Empowering language agents for risk prediction with large-scale clinical tool learning

Author

Listed:
  • Qiao Jin

    (National Institutes of Health (NIH))

  • Zhizheng Wang

    (National Institutes of Health (NIH))

  • Yifan Yang

    (National Institutes of Health (NIH)
    University of Maryland)

  • Qingqing Zhu

    (National Institutes of Health (NIH))

  • Donald Wright

    (Yale University)

  • Thomas Huang

    (Yale University)

  • Nikhil Khandekar

    (National Institutes of Health (NIH))

  • Nicholas Wan

    (National Institutes of Health (NIH))

  • Xuguang Ai

    (Yale University)

  • W. John Wilbur

    (National Institutes of Health (NIH))

  • Zhe He

    (National Institutes of Health (NIH)
    Florida State University)

  • R. Andrew Taylor

    (Yale University
    University of Virginia)

  • Qingyu Chen

    (Yale University)

  • Zhiyong Lu

    (National Institutes of Health (NIH))

Abstract

Clinical calculators play a vital role in healthcare, but their utilization is often hindered by usability and dissemination challenges. We introduce AgentMD, a novel language agent capable of curating and applying clinical calculators across various clinical contexts. As a tool builder, AgentMD first uses PubMed to curate a diverse set of 2,164 executable clinical calculators with over 85% accuracy for quality checks and over 90% pass rate for unit tests. As a tool user, AgentMD autonomously selects and applies the relevant clinical calculators. Our evaluations show that AgentMD significantly outperforms GPT-4 for risk prediction (87.7% vs. 40.9% in accuracy). Results on 698 real-world emergency department notes confirm that AgentMD accurately computes medical risks at an individual level. Moreover, AgentMD can provide population-level insights for institutional risk management. Our study illustrates the capabilities of language agents to curate and utilize clinical calculators for both individual patient care and at-scale healthcare analytics.

Suggested Citation

  • Qiao Jin & Zhizheng Wang & Yifan Yang & Qingqing Zhu & Donald Wright & Thomas Huang & Nikhil Khandekar & Nicholas Wan & Xuguang Ai & W. John Wilbur & Zhe He & R. Andrew Taylor & Qingyu Chen & Zhiyong , 2025. "AgentMD: Empowering language agents for risk prediction with large-scale clinical tool learning," Nature Communications, Nature, vol. 16(1), pages 1-11, December.
  • Handle: RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-64430-x
    DOI: 10.1038/s41467-025-64430-x
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