Project Grant R01HL173866
- This Project Grant award from the National Heart, Lung, and Blood Institute (CFDA 93.837 Cardiovascular Diseases Research) provides $756,906 to the Mayo Clinic to conduct a population-based study on using deep learning techniques to measure breast arterial calcification (BAC) from repurposed mammogram images. The goal is to evaluate the utility of BAC as a biomarker for predicting cardiovascular disease risk in women. The study will analyze data from 125,519 women across two diverse cohorts to...
- This $188,136 Project Grant award from the National Heart, Lung, and Blood Institute (CFDA 93.837 Cardiovascular Diseases Research) supports research to develop an Artificial Intelligence-Enabled Echocardiography Interpretation System (AEIS). The principal investigator, Dr. Chieh-Ju Chao, will collaborate with mentors Dr. Bradley Erickson and Dr. Fei-Fei Li to train visual-linguistic models and large language models to enhance echocardiography interpretation and reporting automation. The goal is...
- This federal Project Grant award of $304,415 from the National Heart Lung and Blood Institute (CFDA 93.837 Cardiovascular Diseases Research) supports the development of a software solution to improve cardiovascular risk prediction using AI analysis of coronary CT calcium score (CTCS) imaging data. The award recipient, Pulseimaging.ai, LLC, is collaborating with researchers from Case Western Reserve University, Houston Methodist, and University Hospitals of Cleveland to create this AI-powered...
- This Project Grant award from the National Heart, Lung, and Blood Institute (NHLBI), under the Cardiovascular Diseases Research program (CFDA 93.837), provides $742,395 to Case Western Reserve University (CWRU) to develop and validate a machine learning-based analysis of coronary artery calcium scans (CTCS) to identify biomarkers for predicting heart failure risk. The 4-year project aims to create an automated tool for extracting CTCS-derived radiomics, develop a comprehensive heart failure risk...
- This Cooperative Agreement award from the Food and Drug Administration (FDA) Research program (CFDA 93.103) provides $1,498,464 to Kaiser Foundation Hospitals to develop and validate AI-enabled echocardiographic biomarkers and integrate real-world electronic health record data to improve early detection and risk stratification of cancer therapy-related cardiac dysfunction (CTRCD). The project aims to transform cardio-oncology care by leveraging a diverse cohort of over 34,000 patients treated...
- This federal Project Grant award of $252,676 from the National Heart Lung and Blood Institute (CFDA 93.837 - Cardiovascular Diseases Research) supports Arizona State University (ASU) in evaluating the efficacy of a Computer Aided Exercise Stress ECG Reader (CAESER) system for automated diagnosis of coronary artery disease. The primary goal is to significantly improve the accuracy of exercise stress electrocardiography in assessing obstructive coronary artery disease across different patient risk...
- This Project Grant award from the National Heart, Lung, and Blood Institute (NHLBI), under the Cardiovascular Diseases Research program (CFDA 93.837), provides $232,500 in funding to The Johns Hopkins University to extend the follow-up period for the Coronary Artery Calcium Consortium (CAC Consortium) study. The goal is to evaluate 30-year survival and cardiovascular mortality risk prediction using coronary artery calcium (CAC) scoring data for individuals aged 30-59, building on the previous...
- This $704,234 federal Project Grant award from the National Heart, Lung, and Blood Institute (CFDA 93.837 Cardiovascular Diseases Research) will support the development of an end-to-end deep learning pipeline for accelerating 4D flow MRI acquisition and automated hemodynamic analysis in patients with bicuspid aortic valve (BAV) disease. The grant will leverage a large database of over 4,000 manually processed 4D flow MRI scans at Northwestern University to train and validate the deep learning...
- The National Heart, Lung, and Blood Institute (NHLBI) awarded a $144,989 Project Grant (CFDA 93.837 - Cardiovascular Diseases Research) to The General Hospital Corporation (doing business as Massachusetts General Hospital) to develop, train, and test deep generative models using computed tomography (CT) images to predict lung injury progression and treatment responses in patients with acute respiratory distress syndrome (ARDS). The goal is to leverage artificial intelligence and image...
- This federal Project Grant award from the National Heart, Lung, and Blood Institute (CFDA 93.837 Cardiovascular Diseases Research) provides $410,956 to Michigan Technological University from September 1, 2025 to August 31, 2028. The funding will support research to develop novel methods for stratifying thrombosis risk in Kawasaki disease patients based on hemodynamic analysis, beyond the use of coronary artery diameter z-scores alone. The project aims to gain a better understanding of the...
This federal Project Grant award from the National Heart, Lung, and Blood Institute (CFDA 93.837 Cardiovascular Diseases Research) will provide $3,918,561 to Kaiser Foundation Hospitals to harness artificial intelligence and deep learning to determine coronary artery calcium estimates in patients with no history of atherosclerotic cardiovascular disease. The study aims to validate a deep learning algorithm for detecting coronary artery calcium on contrast-enhanced CT scans and assess the epidemiology and outcomes of opportunistic screening. It will then test multiple notification strategies to drive statin therapy initiation and minimize patient anxiety, with a focus on historically marginalized racial and ethnic groups. The award period runs from September 2025 through August 2029.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $3.9m | 9/27/25 |