Context-aware monitoring: rethinking comprehensive screening in the era of AI.
Where this comes from
- Record sourced from PubMed, PMID 42587001.
- Also identified by DOI 10.1038/s41746-026-03106-2 and PMC identifier 13470480.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
Abstract
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.