BioTwin-PE: An Uncertainty-Aware Multimodal State-Space Framework and Validation Protocol for Longitudinal Placental Monitoring

Abstract

Placental assessment is necessarily intermittent, while ma- ternal and fetal physiology evolve continuously. This mis- match limits the ability of conventional visit-level prediction models to represent changes occurring between examinations. We present BioTwin-PE, a methods framework for longitu- dinal placental monitoring that combines sparse clinical ob- servations with higher-frequency wearable measurements in an uncertainty-aware state-space model. The framework has two components: an Adaptive Physiological Reconciliation Engine (APRE), which performs reliability-weighted multi- modal assimilation, and a Temporal Placental State Memory (TPSM), which stores filtered and retrospectively smoothed latent states. When a new ultrasound, Doppler, laboratory, or placental oxygenation measurement becomes available, a fixed-lag backward pass revises recent state estimates rather than treating the latest examination as an isolated prediction target. We formalize the observation masks, modality-specific reliability weights, uncertainty propagation, and safety-gated output layer needed for asynchronous clinical data. We further specify a reproducible validation protocol comprising synthetic stress tests, retrospective longitudinal evaluation, missingness and sensor-failure experiments, calibration analysis, subgroup assessment, and clinician review. No clinical efficacy claims are made: this article defines a testable computational method and the evidence required before prospective use. The frame- work is intended to support rigorous investigation of digital- twin methods in computational obstetrics without replacing es- tablished antenatal assessment.