An Enterprise AI Assurance Framework for Biomedical Diagnostics: Integrating a Human Validation Boundary and a Multidimensional Assurance Score into a Lifecycle Governance Model
Artificial intelligence (AI) systems for biomedical diagnostics are usually evaluated on predictive performance, yet clinical adoption also depends on reliability under distribution shift, interpretability, safety behaviour, equity across subgroups, clinician oversight, and post-deployment monitoring. Existing guidelin...