Aligning Clinical Needs and AI Capabilities: A Survey on LLMs for Medical Reasoning
Medical reasoning, clinical competency, and large language models
Qi Peng, Jiatong Li, Sirui Huang, Yiyang Jiang, Kaisong Gong, Ronger Ding, Shijie Ye, Changmeng Zheng, Yi Cai, Xiaobo Yang, Jin Huang, Xiao-Yong Wei, and Qing Li. (2026). Aligning Clinical Needs and AI Capabilities: A Survey on LLMs for Medical Reasoning. Machine Intelligence Research.
About this work
This survey connects clinical practice with computational methods through a dual-view framework. On the clinical side, it develops a five-level competency scheme based on Miller’s Pyramid. On the computational side, it links deductive, inductive, and abductive reasoning to common medical goals and tasks.
The work also introduces a five-level medical reasoning benchmark and evaluates 18 state-of-the-art models, highlighting complementary strengths and persistent gaps in diagnosis, decision support, dialogue, hallucination, and grounding.
Co-first author.