AgentMD: Empowering language agents for risk prediction with large-scale clinical tool learning
- 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 Lu
2025-10-23
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.