AI forecasts patient physiology to optimise IV-to-oral antibiotic switching, published in Nature Communications
ai_ucl · x · 2026-10-13
A UCL-led team published in Nature Communications a clinical AI system for switching patients from intravenous to oral antibiotics. Timely switching shortens hospital stays, reduces catheter-related infections, and cuts costs — yet one in five patients in England remains on IV antibiotics despite meeting switching criteria.
Key design choice: instead of learning from historical decisions (which would reproduce routine delays and inconsistencies), the system uses neural processes to probabilistically model vital sign trajectories, judges switch-readiness against clinical guidelines rather than past behavior, and ranks patients to prioritize clinical review — yielding interpretable outputs. Paper and code are open.
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