Project Grant R21HL175632
- The National Heart Lung and Blood Institute, under its Cardiovascular Diseases Research federal grant program (CFDA 93.837), awarded a $412,250 project grant to Arizona State University (ASU) to develop a real-time, automated smart catheter analyzer for early identification of sepsis through continuous monitoring of urine biomarkers. This non-invasive approach aims to enable rapid sepsis diagnosis, within 200 minutes, to support quick clinical intervention and preservation of heart and lung...
- This federal Project Grant award, with a total funding amount of $304,415.00, was provided by the National Heart, Lung, and Blood Institute (NHLBI) under the Cardiovascular Diseases Research program (CFDA 93.837). The goal of this 1-year project is to develop a software solution that uses artificial intelligence and image analytics to improve cardiovascular risk prediction from screening CT calcium score (CTCS) images. The project team, which includes engineers and clinicians from...
- The federal Project Grant award of $507,000.00 from the National Heart Lung and Blood Institute (CFDA 93.837 - Cardiovascular Diseases Research) aims to develop an automated system that integrates micro-electromechanical sensors, automation, and machine vision to simultaneously measure electrophysiological properties and contractile forces in single human induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs). This innovative system is expected to significantly reduce measurement time...
- This Project Grant award from the National Heart Lung and Blood Institute (CFDA Program 93.837 - Cardiovascular Diseases Research) aims to develop a deep learning-based algorithm to remove cardiopulmonary resuscitation (CPR) artifacts from electrocardiogram (ECG) signals in automated external defibrillators (AEDs). The $752,495 award, active from June 1, 2025 to March 31, 2029, will fund the creation of a database of CPR-contaminated ECG data and the evaluation and optimization of the deep...
- This $150,000 project grant from the National Science Foundation's Computer and Information Science and Engineering program aims to develop technologies to improve cardiac care for patients in rural and tribal areas of Arizona. Clemson University is partnering with Northern Arizona University and community leaders to plan an integrated remote heart monitoring system. The system will utilize deep learning and Markov-based methods to predict deterioration in symptoms for patients with conditions...
- This federal Project Grant award from the National Heart, Lung, and Blood Institute under the Cardiovascular Diseases Research program (CFDA 93.837) provides $793,868 to Tufts Medical Center to develop and validate innovative machine learning methods for automating the diagnosis of aortic stenosis (AS) from cardiac ultrasound imaging. The goal is to improve the identification and treatment of this life-threatening cardiovascular condition that affects over 12.6 million adults annually in 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...
- This $188,136 Project Grant award from the National Heart, Lung, and Blood Institute (NHLBI), under the Cardiovascular Diseases Research program (CFDA 93.837), supports research to develop an Artificial Intelligence-Enabled Echocardiography Interpretation System (AEIS). The principal investigator, Dr. Chieh-Ju Chao, will train with a multidisciplinary mentoring team led by Drs. Bradley Erickson and Fei-Fei Li to advance his skills in visual-linguistic models and large language models. The goal...
- This $117,000 Project Grant award from the National Heart, Lung, and Blood Institute's Cardiovascular Diseases Research program (CFDA 93.837) supports secondary analysis of 3D echocardiographic (echo) images of the right ventricle (RV) to compute 3D surface strain. The goal is to develop enhanced 3D strain analysis techniques that can provide more detailed characterization of RV deformation compared to standard 2D global longitudinal strain (GLS) measures, with the potential to improve...
- This Project Grant award, funded by the National Heart, Lung, and Blood Institute under the Cardiovascular Diseases Research program (CFDA 93.837), supports a feasibility study to assess the use of arteriovenous sampling to evaluate metabolic changes in the heart and legs during exercise in patients with heart failure with reduced ejection fraction. The $242,250 grant, awarded on September 1, 2025, will enable Duke University researchers to leverage interventional cardiologists and...
This federal Project Grant award from the National Heart, Lung, and Blood Institute (CFDA 93.837 - Cardiovascular Diseases Research) to Arizona State University (ASU) aims to evaluate the efficacy of a Computer Aided Exercise Stress ECG Reader (CAESER) for automated diagnosis of coronary artery disease (CAD). The primary goal is to significantly improve the positive predictive value and sensitivity of exercise stress electrocardiography (ESE) in assessing obstructive CAD across various patient risk factors. The $252,676 award, effective from Sep 15, 2025 to Aug 31, 2027, leverages a large harmonized ESE dataset correlated with invasive coronary angiography from multiple cardiac care sites to develop an automated CAD likelihood determination technique from ESE with uniform performance. This work is expected to benefit an ongoing effort in wearable ECG-based CAD risk monitoring for the U.S. workforce.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $252.7k | 9/15/25 |