Feinstein Institutes Receive $3.1 Million NIH Grant to Develop AI-Based Hospital Risk and Prevention Tools


Researchers at The Feinstein Institutes for Medical Research have been granted $3.1 million by the National Institutes of Health (NIH) to conduct a study that aims to utilize artificial intelligence (AI) and machine learning (ML) to monitor hospitalized adult patients and prevent medical deterioration.

Led by Theodoros Zanos, PhD, the study’s goal is to create ML models that can enhance patient monitoring in busy medical and surgical wards, helping identify those at risk of rapid decline and facilitating timely interventions.

The study will tap into Northwell’s extensive clinical dataset, featuring electronic health records from over 2.4 million hospitalizations. Researchers will use this data to develop predictive ML models that support clinicians and nurses in identifying patients at risk of deterioration and those who are more stable. Additionally, continuous monitoring devices like the VitalConnect VitalPatch will be employed to gather and leverage patient data to improve prediction models.

Dr. Zanos, a leader in healthcare AI, has previously worked on projects such as a digital tool that predicts a patient’s overnight stability and a clinical support tool for predicting patient outcomes during COVID-19 care.

This latest project underscores the Feinstein Institutes’ commitment to leveraging technology and AI to improve patient outcomes and reduce health disparities.

The $10 million gift from Scott and Debby Rechler to establish the Scott and Debby Rechler Center for Health Outcomes within the Institute of Health System Science also reflects the institute’s dedication to advancing healthcare through technological innovation.

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