O'Sullivan LLM (cardiology)
A Large Language Model for Complex Cardiology Care
Patient / Population Intervention / Exposure Comparison Outcome
In 9 general cardiologists assessing complex suspected genetic cardiomyopathy, an LLM assistant alongside the raw investigations improved blinded subspecialist-rated quality of triage, diagnosis and management compared with cardiologists working unassisted.
N
9patients
Design
RCT, cardiologists randomised, retrospective real-world case data, blinded subspecialist rating
Endpoint
Blinded subspecialist preference across a ten-domain rubric of triage, diagnosis and management quality
Relevance
2Important — one of several pillars.
ResultSubspecialists preferred AMIE-assisted assessments 46.7% vs 32.7% for cardiologists alone (P=0.02; 20.6% ties). Clinically significant errors 13.1% vs 24.3% (P=0.033); missing content 17.8% vs 37.4% (P=0.0021).
O'Sullivan JW, et al. Nat Med. 2026;32(2):616-623. 10.1038/s41591-025-04190-9
Discussion & critique
Extends the AMIE programme from simulated primary care (AMIE) into a subspecialty where expertise is scarce, with the LLM reading raw diagnostic data rather than text alone. Only nine cardiologists, retrospective cases from a single subspecialist practice, preference-based rubric scoring by three raters, and no patient outcomes — a signal for augmentation, not evidence of benefit.