Use Case / Pregnancy

DT4H supports pregnancy workflows through trimester-aware longitudinal context.

The pregnancy use case connects care history, trimester context, recovery, symptoms, stress, sleep, and SETPOINT feedback into a bounded calibrated Twin.

Pregnancy model flow #

SIGNALSPregnancy Context

Trimester · symptoms · vitals · labs · sleep · recovery

DT4HPregnancy Twin

Cohort priors · care history · reference context · calibration

STATEKCurrent State

Confidence · trajectory · readiness · review posture

SETPOINTSupport Loop

Practices · education · check-ins · outcomes

Signal domains #

01

Trimester context

State interpretation changes across trimester and care phase.

02

Symptoms + recovery

Fatigue, nausea, sleep, stress, movement, and recovery patterns.

03

Clinical history

Prior pregnancies, risk context, labs, medication, and visit patterns.

04

Behavior support

Hydration, movement, breathing, rest, and education practices.

05

Care coordination

Clinician review, escalation boundaries, and workflow continuity.

06

Outcome feedback

Check-ins and practice outcomes recalibrate the Twin over time.

Clinical boundaries #

Appropriate Role

Supportive longitudinal layer

  • Track non-diagnostic longitudinal context.
  • Support care continuity and patient education.
  • Surface confidence and signal freshness.
  • Preserve clinician review boundaries.
Boundary

Not autonomous pregnancy care

  • Not fetal or maternal diagnosis.
  • Not triage replacement.
  • Not emergency guidance.
  • Not substitute for prenatal care.
LayerGovernance Framework
StatusActive Draft
SystemDT4H / StateK / SETPOINT
BoundaryInfrastructure, not diagnosis
System lineageDT4HTwinStateKSETPOINTOutcomesRecalibration
Infrastructure boundaryDT4H models cohorts, Twins, calibration, and runtime state. It does not diagnose, prescribe, or replace licensed clinical judgment.
Document statusInfrastructure draft
Last updatedMay 2026
Applies toDT4H.ai / AvatarK.ai ecosystem