Project Grant R01LM014731
Award Date 9/15/25
Completion Date 8/31/29
Dollars Obligated $3.5M
Federal Agency
Federal Grant Program
Assistance Type
Project Grant
Place of Performance
California, USA
Similar Awards
- This Project Grant award from the National Institute on Drug Abuse (NIDA), under the Drug Use and Addiction Research Programs (CFDA 93.279), provides $191,700.00 to Cedars-Sinai Medical Center to develop and validate an AI-driven framework to efficiently predict and identify severe opioid adverse drug effects, including persistent use and related post-surgical outcomes, from electronic health record (EHR) data. The project aims to leverage automated machine learning, knowledge graphs, and...
- This federal Project Grant award of $376,184, provided by the National Institute of Environmental Health Sciences under the Medical Library Assistance program (CFDA 93.879), aims to investigate how integrating outside patient data into clinical workflows can improve healthcare outcomes and reduce costs. The key focus is on understanding how clinicians use data from health information exchanges (HIEs) and the value of that data for improving utilization, quality, and patient satisfaction. The...
- This Project Grant award of $1,526,628.00 from the National Heart Lung and Blood Institute (CFDA 93.837 Cardiovascular Diseases Research) supports research by Cedars-Sinai Medical Center to develop Artificial Intelligence (AI) methods for analyzing echocardiography data to predict biological cardiovascular age and identify trajectories of accelerated versus delayed cardiovascular aging. The research aims to capture an aggregate measure of cardiac aging and identify potential interventions to...
- The federal Project Grant award of $2,720,667 from the National Institute of Environmental Health Sciences (CFDA 93.879 - Medical Library Assistance) will fund research at Yale University to develop robust algorithms and a tool to help clinicians and life scientists better understand the estimates of predictive models by visualizing patient neighborhoods based on supervised weighted distances. The goal is to increase trust in complex, multivariate predictive models used in clinical AI and...
- This federal Project Grant award of $402,750 from the National Institute of Environmental Health Sciences under the Medical Library Assistance program (CFDA 93.879) supports the development of large language models (LLMs) for drug safety and effectiveness causal analysis using real-world data from electronic health records (EHRs). The primary objective is to build an LLM-based causal analytical platform that can robustly determine a wide variety of clinical phenotypes, including those not...
- This $351,000 federal Project Grant award from the National Institute of Environmental Health Sciences (CFDA 93.879 - Medical Library Assistance) supports research to measure and improve the innovative potential of biomedical research and translation. The project develops computational, data, and network science tools integrated with a social science framework to analyze discovery and innovation dynamics, with the goal of accelerating transformative breakthroughs in biomedical fields. The...
- This federal Project Grant award of $410,924 was provided by the National Institute of Environmental Health Sciences (NIEHS) under the Medical Library Assistance program (CFDA 93.879) to fund the development of QUALLM, an innovative automated toolset that leverages Fast Healthcare Interoperability Resources (FHIR) and generative artificial intelligence (GenAI) to enable real-time abstraction and evaluation of clinical quality measures. The goal is to revolutionize healthcare quality...
- The National Science Foundation awarded a $598,676 project grant to Beth Israel Deaconess Medical Center, Inc. to develop machine learning-driven user interfaces for medical record information gathering and synthesis under the Computer and Information Science and Engineering federal grant program (CFDA 47.070). The award period is from September 1, 2022 to August 31, 2026. The project will advance the foundations of human-AI interaction and artificial intelligence for healthcare by developing...
- The federal Project Grant award of $1,602,000.00 from the National Institute of Environmental Health Sciences, under the Medical Library Assistance program (CFDA 93.879), will support the development of computational methods for analyzing multiplex immunofluorescence (MIF) imaging data to study the tumor microenvironment. The project aims to leverage a unique MIF dataset from over 2,000 cancer patients across 20 tumor types to develop innovative computational strategies, including spatial...
- This $696,824 federal Project Grant award from the National Institute of Biomedical Imaging and Bioengineering (NIBIB), under the Discovery and Applied Research for Technological Innovations to Improve Human Health program (CFDA 93.286), supports research at the University of North Carolina at Chapel Hill (UNC-CH) to develop robust and interpretable multi-modal AI/ML models for precision medicine. The project aims to address key challenges in integrating complex, heterogeneous biomedical data...