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AI analyzes data from home monitoring devices (e.g. BP, glucose, wearables) to generate personalized risk scores. Aggregated trends help identify at-risk cohorts across populations for early intervention.
Generative AI summarizes thousands of home care plans and their outcomes to recommend improvements in chronic disease management protocols across a population.
Patient inputs from home (symptoms, journals, teleconsults) are interpreted by AI to flag individual risks. Patterns across multiple patients trigger population-level alerts for emerging health issues.
AI extracts social and environmental risk factors (e.g., food insecurity, housing) from unstructured caregiver and nurse visit notes.
