Project Grant R44OD024874

This Project Grant award from the National Heart Lung and Blood Institute (NHLBI), under the Cardiovascular Diseases Research program (CFDA 93.837), provides $343,203 to Cyion Technologies LLC to develop a novel in vitro electrophysiology system for high-throughput measurement of intracellular action potential (IAP) in human-derived cardiomyocytes. The system leverages a 3D nanoelectrode array (NEA) technology to enable scalable recordings of IAP signals from many individual cardiomyocytes. This...

The National Science Foundation awarded Cardiophi LLC $532,000 under the Technology, Innovation, and Partnerships program to develop an artificial intelligence solution for the automated interpretation of electrocardiograms. The project aims to refine existing deep learning-based algorithms for detecting irregular heartbeats, develop methods for predicting the onset of cardiac arrhythmias, and create interpretable and explainable tools to provide insights from ECG signals to clinicians....

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 Project Grant award of $174,990 from the National Science Foundation (CFDA 47.070 Computer and Information Science and Engineering) to Yeshiva University aims to develop novel deep learning models and software for the automated detection and diagnosis of cardiomegaly (enlargement of the heart) in animals. The key products and services to be delivered under this 2-year award include: Novel deep learning models that can accurately detect cardiomegaly while aligning with traditional clinical...

This National Science Foundation (NSF) Small Business Technology Transfer (STTR) Phase I award provides $275,000 to Neuraltrak, Inc. to develop and validate a method for continuous, real-time cardiac rhythm diagnosis and display using high-quality atrial electrogram data. The project aims to address limitations of current post-operative cardiac rhythm monitoring approaches, which often fail to accurately interpret rhythm due to poor atrial signal quality and patient variability. The...

This $1,344,373 Project Grant award from the National Institutes of Health (NIH) under the Trans-NIH Research Support program (CFDA 93.310) supports research to investigate cardiac regeneration in human cells and zebrafish models. The primary objectives are to: (I) assess the dynamic gene regulatory networks involved in zebrafish heart regeneration using single-cell ATAC-seq, (II) interrogate the reactivation of developmental gene programs in human cardiac organoids after injury using multiomics...

The National Science Foundation (NSF) awarded a $275,000 Phase I Small Business Innovation Research (SBIR) grant under the NSF Technology, Innovation, and Partnerships (CFDA 47.084) program to KAI TECH LLC. The funding supports the development of an advanced software system called ECG-AID for automated electrocardiogram (ECG) analysis and interpretation. The ECG-AID prototype integrates a comprehensive ECG database, Z-score-based assessments, and machine-learning techniques to enhance the...

This Project Grant award of $608,944, provided by 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), aims to develop an AI-assisted strategy for monitoring pulmonary congestion in acute heart failure patients in emergency settings. The primary goal is to automate lung ultrasound congestion scoring using AI/ML methods and a high-quality dataset of heart...

This Project Grant award from the National Heart, Lung, and Blood Institute (NHLBI), under the Cardiovascular Diseases Research program (CFDA 93.837), provides $752,495 to the University of Connecticut to develop a deep learning-based method for removing cardiopulmonary resuscitation (CPR) artifacts from electrocardiogram (ECG) signals. The goal is to enable continuous CPR delivery during automated external defibrillator (AED) use, while maintaining accurate cardiac rhythm analysis and shock...

This Project Grant award from the National Heart, Lung, and Blood Institute (NHLBI), under the Cardiovascular Diseases Research program (CFDA 93.837), provides $293,653 to 3DT Holdings, LLC to develop a software tool for optimizing cardiac resynchronization therapy (CRT), conduction system pacing (CSP), and left ventricular endocardial pacing (LVEP) therapies. The goal is to reduce non-responder rates and improve patient identification for these treatments, especially for patients with...