DT4H separates signal ingestion, cohort intelligence, reference-human modeling, Twin initialization, calibration, state computation, and SETPOINT execution into a layered architecture.
Biomarkers, behavior, clinical context, and self-report enter the modeling system.
Individuals are mapped into probabilistic population contexts.
Cohort-derived priors define expected ranges, variance, and trajectories.
DT4H builds a person-specific model from individual data and cohort priors.
New evidence updates confidence, state, trajectory, and model accuracy.
State is operationalized into protocols, practices, outcomes, and recalibration.