Use Case / Fertility

DT4H supports fertility workflows by preserving longitudinal readiness context.

The fertility use case connects cycle context, metabolic state, stress, recovery, prior care history, referrals, and SETPOINT feedback into a calibrated Twin.

Fertility model flow #

SIGNALSReadiness Context

Cycle · metabolic · stress · sleep · labs · history

DT4HFertility Twin

Cohort priors · reference ranges · calibration state

STATEKReadiness State

Confidence · trajectory · transition readiness

SETPOINTSupport Loop

Preparation · practices · outcomes · recalibration

Signal domains #

01

Cycle pattern

Cycle regularity, phase context, symptoms, and timing continuity.

02

Metabolic readiness

Energy, weight trend, glucose-related context, inflammation, and recovery.

03

Stress + recovery

Sleep consistency, stress load, resilience, and nervous-system regulation.

04

Care pathway

OBGYN history, referrals, fertility consults, lab context, and prior interventions.

05

Protocol adherence

Practice completion, lifestyle readiness, education, and support behaviors.

06

Outcome feedback

Observed changes update confidence, trajectory, and model calibration.

Continuity value #

Before referralContext formation

Builds longitudinal readiness history before specialty care.

During referralKnowledge continuity

Preserves context when patients move from OBGYN to fertility workflows.

During supportExecution feedback

Tracks practices, symptoms, adherence, and outcome signals.

After outcomesRecalibration

Updates Twin confidence and future readiness interpretation.

Boundary note #

Not fertility diagnosis

DT4H does not diagnose infertility or replace fertility specialists.

Readiness, not prediction certainty

Readiness state is a bounded modeling signal, not deterministic prognosis.

Useful pilot bridge

This use case is valuable when patients transfer from OBGYN care into fertility or IVF pathways.

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