NLP extracts screening gaps from clinical notes that structured data alone cannot find.
LLMs now match human experts on clinical summarization, but only for specific, bounded tasks.
Tracking biological age changes over time predicts mortality better than single snapshots.
Multiple cortisol tests at different times reveal HPA dysfunction that single draws miss.
Blood tests reveal most Americans lack omega-3 levels needed to prevent heart disease.
Combining CRP with IL-6 and immune markers reveals which inflammatory pathways actually drive risk.
Continuous glucose monitors reveal hidden glucose swings in metabolically healthy adults.
Particle count, not cholesterol mass, better predicts heart attack and stroke risk.
A cheap genetic test catches the one-in-five adults at hidden heart risk.
Variability within a person's biomarker readings signals disease before trend lines do.
Labs must decide what genetic findings to report and patients need clear consent choices.
Companies market genetic tests with confidence that science hasn't earned yet.
