Federal Project Grant Award Summary

The University of Pittsburgh received a $676,469 Project Grant award dated July 10, 2026, from the National Institute of Child Health and Human Development (NICHD) under the Child Health and Human Development Extramural Research program (CFDA 93.865). This five-year initiative, extending through June 30, 2031, will develop and implement artificial intelligence-driven tools to enable precision rehabilitation for post-stroke patients. The project addresses a critical clinical gap by creating natural language processing (NLP) algorithms to extract rehabilitation data from electronic health records (EHRs), alongside predictive models that integrate both structured and unstructured EHR data. These deliverables will enable clinicians to prescribe personalized, optimized rehabilitation exercises—including specific dosages and timing—tailored to individual patient characteristics and recovery patterns.

The project encompasses three primary aims: development of a rehabilitation ontology and ontology-based NLP algorithms; creation of predictive models for personalized rehabilitation recommendations to maximize functional outcomes; and validation of the NLP and predictive models using the ENACT Network. By bridging existing research gaps in EHR data analytics and predictive modeling, the project aims to enhance clinical outcomes and reduce lifetime healthcare expenses for the estimated 9.4 million adults in the United States living with stroke-related disability.