The accuracy-safety trade-off of large reasoning models in clinical diagnostics

A study evaluated large reasoning models (LRMs) against large language models (LLMs) on clinical diagnosis using the AIMS-LDR benchmark. LRMs showed higher accuracy in primary diagnoses but produced more false positives and had lower reproducibility. Combining LRMs with clinician verification improved diagnostic accuracy.