This $163,034 Project Grant award from the National Heart, Lung, and Blood Institute (NHLBI) under the Cardiovascular Diseases Research program (CFDA 93.837) will support the development of deep learning-based artificial intelligence (AI) algorithms to improve resuscitation of out-of-hospital cardiac arrest (OHCA) patients. The principal investigator, Dr. Jason Coult, will leverage large retrospective datasets of OHCA defibrillator recordings to 1) design AI algorithms that can identify specific...
This $729,821 Project Grant award from the National Institute of Environmental Health Sciences (NIEHS) under the Medical Library Assistance (CFDA 93.879) program supports the development of artificial intelligence (AI) and machine learning (ML) methods for real-time monitoring and updating of clinical decision support (CDS) systems. The goal is to reduce health disparities that may arise from the use of CDS tools. The key products of this work include: Fair ML models trained on retrospective...
This federal Project Grant award, totaling $753,813 and provided by the National Heart Lung and Blood Institute (CFDA 93.837 Cardiovascular Diseases Research), supports research to develop novel machine learning techniques for predicting cardiovascular outcomes in patients with clonal hematopoiesis of indeterminate potential (CHIP). The key goals are to use cardiac MRI imaging and genomic data to: 1) Develop a machine learning model to accurately identify CHIP patients and predict their risk...
This Project Grant award of $641,544 from the National Heart, Lung, and Blood Institute (NHLBI) under the Cardiovascular Diseases Research program (CFDA 93.837) supports research to develop enhanced machine learning tools for analyzing complex biomedical data related to heart, lung, blood, and sleep (HLBS) disorders. The key objectives are to: 1) propose novel machine learning methods to reveal causal relationships between clinical features and health/disease outcomes while adjusting for complex...
This Project Grant award from the National Heart, Lung, and Blood Institute (NHLBI), under the Cardiovascular Diseases Research program (CFDA 93.837), provides $299,604 to Case Western Reserve University to develop and validate a novel transfer volume regression model. This model aims to enable quantitative clinical risk predictions for major cardiovascular events, including stroke, heart attack, heart failure, and death. The project will leverage commonly used, low-cost screening programs to...
The federal Project Grant award R01HL173531, totaling $737,815, was provided by the National Heart, Lung, and Blood Institute (NHLBI) under the Cardiovascular Diseases Research federal grant program (CFDA 93.837). The award supports the development and validation of an automated electronic health record (EHR)-embedded Clinical Classifier Model (CCM) system to rapidly identify distinct molecular phenotypes of acute respiratory distress syndrome (ARDS) and sepsis at the bedside. This will enable...
This Project Grant award from the U.S. Department of Health and Human Services' Agency for Healthcare Research and Quality (AHRQ) under the CFDA 93.226 Research on Healthcare Costs, Quality and Outcomes program is funding the development and testing of a clinical decision support (CDS) tool to improve iron deficiency screening and management for pregnant individuals at high risk of postpartum hemorrhage (PPH). Specifically, the $118,089 award will support a two-phase project at Massachusetts...
This $1,527,766 Project Grant awarded by the National Heart, Lung, and Blood Institute (CFDA 93.837 Cardiovascular Diseases Research) seeks to develop, validate, and demonstrate the impact of a novel in-hospital mortality prediction model (MPM) that optimizes fairness across key subgroups defined by demographic and socioeconomic factors. The objectives are to: Develop fairness-informed in-hospital MPMs by identifying predictive features, assessing missing data bias, and implementing bias...
This federal Project Grant award of $165,364 from the National Heart, Lung, and Blood Institute (NHLBI) under the Cardiovascular Diseases Research program (CFDA 93.837) aims to identify novel ambulatory blood pressure patterns and genomic risk factors to enhance cardiovascular disease (CVD) prediction and management among young adults aged 18-39. The project, led by Dr. Cho, a cardiovascular epidemiologist, will leverage multiethnic population-based cohorts, large-scale genomics, and...
This federal Project Grant award from the National Institutes of Health (NIH) Office of the Director under the Trans-NIH Research Support program (CFDA 93.310) aims to develop an AI-augmented, image-based hemodynamic modeling platform to enhance cardiovascular research and healthcare. The $150,000 award, effective September 1, 2024 through May 31, 2028, will be used by the University of Notre Dame to automate the transformation of medical images into 3D geometries for computational fluid...