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...
The federal Project Grant award R43HL177950 was provided by the National Heart, Lung, and Blood Institute (NHLBI) under the Cardiovascular Diseases Research program (CFDA 93.837). The $793,956 grant, awarded on January 1, 2025, supports the development of innovative solutions to improve survival rates for patients experiencing refractory cardiac arrest, which accounts for over 750,000 annual deaths in the U.S. The project, led by Resuscitation Innovations LLC (UEI: G621SSW9F3L5), aims to advance...
The National Heart, Lung, and Blood Institute (NHLBI) awarded a $429,153 Project Grant under the Cardiovascular Diseases Research program (CFDA 93.837) to Michigan Technological University. The funding supports research to improve patient selection and left ventricular lead placement for cardiac resynchronization therapy (CRT) by integrating analysis of electrical dyssynchrony on ECG and mechanical dyssynchrony on gated SPECT myocardial perfusion imaging. The project aims to use unsupervised...
The federal Project Grant award R21HL172209, funded by the National Heart, Lung, and Blood Institute (NHLBI) under the Cardiovascular Diseases Research program (CFDA 93.837), supports research to apply machine learning techniques to analyze longitudinal changes in electrocardiogram (ECG) data for individuals with congenital heart disease. The $117,375 award, effective from August 1, 2024 to July 31, 2026, aims to identify ECG biomarkers that can predict the need for cardiac intervention or...
This federal Project Grant award, issued by the National Heart, Lung, and Blood Institute (NHLBI) under the Cardiovascular Diseases Research program (CFDA 93.837), provides $704,611 to The Trustees of Columbia University in the City of New York to develop and validate a deep learning model, named EchoNext, that can accurately detect undiagnosed structural heart disease from electrocardiogram (ECG) waveforms. The goal is to enable effective and equitable diagnosis of structural heart disease,...
The National Heart, Lung, and Blood Institute (NHLBI), a division of the National Institutes of Health (NIH), awarded a $294,023 Project Grant (CFDA 93.837 Cardiovascular Diseases Research) to Heartlung Corporation to develop the AUTOCHAMBER AI tool. AUTOCHAMBER is designed to opportunistically screen existing chest CT scans for early detection of enlarged cardiac chambers and left ventricular hypertrophy, which can indicate risk of atrial fibrillation, stroke, and heart failure. The project...
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...
The National Heart, Lung, and Blood Institute (NHLBI) awarded a $295,153 Project Grant under the Cardiovascular Diseases Research program (CFDA 93.837) to Safebeat RX Inc. The funding supports the development of a novel, smartwatch-enabled technology that allows patients with low-risk atrial fibrillation to safely initiate antiarrhythmic medications at home. The technology analyzes post-drug ECG data taken by patients using a machine learning algorithm and provides this information to...
This federal Project Grant award of $393,750 from the National Heart, Lung, and Blood Institute (NHLBI) under the Cardiovascular Diseases Research program (CFDA 93.837) supports a research project focused on developing a computational approach for predicting and preventing arrhythmias, a leading cause of sudden cardiac death. The project aims to discover effective antiarrhythmic drug therapies and optimal clinical markers for arrhythmia risk prediction by leveraging mathematical modeling,...
This federal Project Grant award from the National Heart, Lung, and Blood Institute (NHLBI) under the Cardiovascular Diseases Research program (CFDA 93.837) totaling $671,544 supports research to develop cardiac ultrasound radiomics-guided deep neural networks for acute myocardial infarction (AMI) precision phenotyping. The project aims to integrate cardiac ultrasound radiomics, conventional echocardiography, and clinical data using deep learning to improve risk assessment and prognosis for...