Context-aware monitoring: rethinking comprehensive screening in the era of AI

Applying advanced measurement technologies proactively in asymptomatic populations predictably yields false positives, as a consequence of Bayes’ Theorem. Yet the same Bayesian arithmetic suggests a remedy: adding context. Serial and multimodal measurements, integrated using context-aware AI that prioritizes within-person change over population norms, can reduce false positive rates while preserving sensitivity. We describe early illustrations from imaging and molecular diagnostics and discuss challenges including cost, anxiety, liability, and equity.