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Foundations for Next-Generation Intrapartum Decision Support via Fusion of Selective State-Space Models

Award Number: R01HD123035
ORGANIZATION: NATIONAL INSTITUTE OF CHILD HEALTH AND HUMAN DEVELOPMENT
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)
PERIOD OF PERFORMANCE START DATE: 09/15/2026
PERIOD OF PERFORMANCE END DATE: 08/31/2031

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Foundations for Next-Generation Intrapartum Decision Support via Fusion of Selective State-Space Models - Project Summary / Abstract Electronic fetal monitoring (EFM) remains the standard of care during delivery, yet subjective interpretation and poor calibration limit its reliability. Despite decades of widespread use, preventable adverse neonatal outcomes and unnecessary operative interventions remain unacceptably common. Current tools provide neither calibrated, real-time probabilities of fetal well-being nor transparent explanations that clinicians can trust. This project will establish the foundations for next-generation intrapartum decision support by creating a probabilistic framework that fuses selective state-space models (SSSMs) to deliver calibrated, interpretable, and clinically aligned assessments of fetal well-being. Selective state-space models are modern sequence models that process signals step by step with linear computational and memory cost, which makes them ideally suited for accurate, low-latency analysis of long fetal heart rate (FHR) and uterine activity (UA) recordings. Unlike older approaches that oversimplify long recordings or slow down under heavy data loads, SSSMs combine speed, robustness, and accuracy in a single framework. They can track hours of physiological signals in real time, adapt to missing or noisy inputs without failure, and provide a continuous bedside index that clinicians can trust. This balance of efficiency and reliability gives SSSMs unique power as a foundation for decision support in the delivery room, where every second counts. The proposed system will integrate a bank of SSSMs with adaptive fusion that adjusts weights by data quality and relevance, identifies deviations from healthy baselines, and preserves calibration under noisy or incomplete conditions. Each output will include a probability of well-being, confidence bands that reflect uncertainty, and an explanation vector that indicates the contribution of key features. Specific Aim 1 will establish real-time probabilistic methods to assess fetal well-being and short-term progno- sis during delivery using FHR, UA, and relevant clinical context. Specific Aim 2 will deliver calibrated uncertainty estimates and transparent explanations aligned with clinical risk and decision thresholds. Specific Aim 3 will expand and standardize public FHR resources by incorporating antenatal and structured clinical information to support reproducible validation. The expected outcomes include a clinician-aligned index of fetal well-being with transparent uncertainty quantification, validated fusion methods for robust intrapartum assessment, and a shareable dataset for the broader research community. Collectively, these advances will set the stage for a new generation of intrapartum decision support that strengthens clinical confidence, reduces unnecessary interventions, improves neonatal outcomes, and redefines how data-driven intelligence supports childbirth.


Issue Date FY	Funding FY	Legal Entity Name	Legal Entity Address	Legal Entity City	Legal Entity State	Legal Entity Zip Code	Legal Entity COUNTY	Legal Entity COUNTRY	Assistance Listing	Award Code	Budget Year	Action Date	Action Type	Action Amount

Issue Date FY: 2026 ( Subtotal = $677,340 )
2026	2026	THE RESEARCH FOUNDATION FOR THE STATE UNIVERSITY OF NEW YORK	W5510 FRANKS MELVILLE MEMORIAL LIBRARY	STONY BROOK	NY	11794	SUFFOLK	USA	Child Health and Human Development Extramural Research	000	1	9/17/2026	NEW	$677,340
														Subtotal = $677,340

Grand Total All Awards = $677,340

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Foundations for Next-Generation Intrapartum Decision Support via Fusion of Selective State-Space Models

Award Number: R01HD123035

ORGANIZATION: NATIONAL INSTITUTE OF CHILD HEALTH AND HUMAN DEVELOPMENT

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

PERIOD OF PERFORMANCE START DATE: 09/15/2026

PERIOD OF PERFORMANCE END DATE: 08/31/2031

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