Figure 2.

Digitally Augmented Perception, Action, and Cognition in a Learning Health System

AI-enabled capabilities have the potential to augment the sensory, motor, and cognitive aspects of an LHS. Perception expands sensing through: 1) opportunistic sensing from routine tests and reports; 2) remote monitoring via wearables and implanted sensors that stream physiologic data; and 3) vocal biomarkers and ambient listening that convert clinician–patient dialogue into structured information. Action translates signals into decisions via: 1) digital nudges that support guideline-concordant therapy and quality improvement; 2) risk alerts that surface early deterioration to care teams; and 3) diagnostic dialogues that return individualized, evidence-grounded recommendations. Cognition closes the loop by: 1) simulation with digital twins for procedural planning and forecasting; 2) LLM-assisted trial recruitment; and 3) trial emulation and adaptive enrichment using real-world data to generate timely evidence.