Clinical AI tools are losing to general-purpose models
Open almost any surgical journal this year and you’ll find a new AI model. A neural network that predicts anastomotic leak. A risk calculator trained on a single institution’s registry. A computer-vision system that labels the phases of a laparoscopic cholecystectomy. A bespoke tool for predicting graft patency, rupture risk, or readmission. Each is presented as a small, hard-won victory where domain experts encode clinical knowledge into a tightly scoped …
Clinical AI tools are losing to general-purpose models
