Project Grant R01HL176883
- This Project Grant award from the National Heart, Lung, and Blood Institute (CFDA 93.837 Cardiovascular Diseases Research) provides $197,640 to Dr. Lee Goeddel at Johns Hopkins University to conduct research on the relationship between cardiac output, renal perfusion, and the development of acute kidney injury in cardiac surgery patients. The project aims to leverage Dr. Goeddel's expertise in data science, biomarkers, and ultrasound imaging to better understand the mechanisms behind this...
- This $146,013 Project Grant award from the National Heart Lung and Blood Institute under the Cardiovascular Diseases Research program (CFDA 93.837) will be used by The Medical College of Wisconsin, Inc. to establish a large patient cohort leveraging electronic health record and administrative claims data to determine the risks of cardiopulmonary and renal end organ complications and factors associated with frequent acute care use among individuals with sickle cell disease. The award period...
- This federal Project Grant award, totaling $813,284.00 and provided by the National Heart, Lung, and Blood Institute (CFDA 93.837 Cardiovascular Diseases Research), supports a research study on the relationship between acute kidney injury (AKI) and delirium in patients who have undergone cardiac surgery. The key objectives of this 5-year study are to: 1) determine the incidence and clinical characteristics of AKI-associated delirium in cardiac surgery patients, 2) delineate the signaling...
- 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 federal Project Grant award of $193,984 from the National Heart Lung and Blood Institute (CFDA 93.837 Cardiovascular Diseases Research) supports research to investigate the interplay between inflammation, angiogenesis, myocardial perfusion, and myocardial function in patients with advanced chronic kidney disease (CKD). The project, conducted by Brigham & Women's Hospital Inc., aims to mechanistically explore cardiovascular health before and after kidney transplantation. Key objectives...
- This $1,302,060 federal Project Grant awarded by the National Institute of Biomedical Imaging and Bioengineering (NIBIB) under the Discovery and Applied Research for Technological Innovations to Improve Human Health (CFDA 93.286) program aims to develop an AI-assisted strategy for monitoring pulmonary congestion in acute heart failure patients in emergency settings. The primary goals are to automate lung ultrasound congestion scoring using AI/ML methods and a dataset of heart failure patients,...
- 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 federal Project Grant award of $169,344 from the National Heart Lung and Blood Institute (CFDA 93.837 Cardiovascular Diseases Research) aims to advance the management of critically ill adults with non-ARDS acute hypoxemic respiratory failure (NAHRF). The key objectives are to: 1) Develop clinical prediction models for mortality in NAHRF patients; 2) Apply machine learning to detect NAHRF subphenotypes associated with differential clinical outcomes; and 3) Use sequencing-based whole...
- This federal Project Grant award of $1,479,335.00 from the National Heart Lung and Blood Institute under CFDA 93.837 Cardiovascular Diseases Research aims to leverage observational data and advanced machine learning methods to address gaps in understanding and personalizing treatment for Acute Respiratory Distress Syndrome (ARDS). The key products and services to be delivered include: Developing improved methods for ARDS phenotyping using dynamic clinical data to better understand prognosis...
- This Project Grant award from the National Heart Lung and Blood Institute, under the Cardiovascular Diseases Research federal grant program (CFDA 93.837), provides $186,408 to the University of Washington to develop robust models that identify patients at high risk for persistent hypoxemic respiratory failure (HRF). The goal is to improve the ability to distinguish patients with persistent HRF early, which is critical for enrolling the highest-risk patients in clinical trials for new HRF...
This Project Grant award from the National Heart, Lung, and Blood Institute (CFDA 93.837 Cardiovascular Diseases Research) to Baylor College of Medicine aims to leverage machine learning analysis of electronic medical record data to develop new clinical decision support tools for early prediction and mitigation of acute kidney injury (AKI) after cardiac surgery. The $613,399 award, made on September 16, 2025, will support the development of personalized machine learning algorithms and real-time risk monitoring capabilities to enable targeted interventions and improve patient outcomes. The project seeks to address the high incidence of AKI, a frequent and serious complication of cardiac surgery that is associated with increased mortality, length of stay, and hospital costs. By providing early AKI prediction and data-driven intervention recommendations, this initiative aims to enhance clinical decision-making and mitigate the burden of AKI in the post-cardiac surgery critical care setting.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $613.4k | 9/16/25 |