Proposed Three-Layer AI Framework Aims to Make Clinical Decision Support More Transparent

A new article proposes a clinical decision support architecture that combines rule-based protocols, Bayesian reasoning, and time-series prediction, with physicians kept as final decision-makers. It argues that current systems often act as opaque black boxes, which fuels alert fatigue and clinician distrust. The authors recommend judging clinical usefulness through outcome-action pairing and decision-curve metrics rather than accuracy alone. The piece also reviews regulatory requirements, including the EU AI Act and FDA guidance classifying such software by risk, and it addresses ethical principles and bias mitigation.