Project Grant R01EB037101
- This $319,942 Project Grant awarded by the National Science Foundation (CFDA 47.084 - NSF Technology, Innovation, and Partnerships) to the University of North Carolina at Chapel Hill (UNC-CH) focuses on building a collaborative and transparent open-source ecosystem to strengthen the reliability of artificial intelligence (AI) applications in healthcare. The project aims to enhance the safety, robustness, and interpretability of medical AI systems by developing shared infrastructure, governance...
- This National Science Foundation project grant of $260,000 supports research at the University of North Carolina at Chapel Hill to develop statistical analysis frameworks for precision medicine incorporating abundant data features. Funded under the Mathematical and Physical Sciences program (CFDA 47.049), the three-year award running from August 2022 to July 2025 will adapt semi-parametric and reinforcement learning methods to precision medicine scenarios involving medical images, genetic...
- This $300,000 Project Grant award from 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), supports the development of interpretable machine learning tools to uncover imaging biomarkers associated with breast and lung cancer. The project aims to create dimension reduction techniques to visualize features from deep learning models, establish an interpretable...
- This federal Project Grant award for $653,230.00, 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), supports the development of MED-SCALLOP - a novel neurosymbolic AI methodology and software tool. The goal is to create inherently explainable AI/ML models for clinical decision support in healthcare, which can effectively integrate deep neural...
- This federal Project Grant award of $426,479 from the National Institute of General Medical Sciences (NIGMS), under the Biomedical Research and Research Training program (CFDA 93.859), will support research toward developing statistical and computational tools to enable precision risk stratification, diagnosis, and treatment of medical conditions. The research will focus on integrating and synthesizing data from diverse sources such as biobanks, electronic health records, and clinical registries...
- The University of North Carolina at Chapel Hill was awarded a $401,155 Project Grant from 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). The 4-year grant, commencing on July 1, 2025, aims to develop the first knowledge-empowered deep learning pipeline for accurate and consistent processing and analysis of lifespan brain MRI data from various large-scale...
- This National Science Foundation (NSF) Project Grant, awarded under the Computer and Information Science and Engineering program (CFDA 47.070), provides $220,000 to Yale University from September 1, 2023 through August 31, 2027. The project aims to develop a smarter artificial intelligence (AI) system to better understand and analyze complex medical images, such as those from multiple scans of a patient. The research team will tackle challenges to make the AI system more scalable, interpretable,...
- The University of California, San Francisco (UCSF) was awarded a $1,453,500 Project Grant by the National Institutes of Health (NIH) under the Trans-NIH Research Support program (CFDA 93.310). The funding will support the development of a novel, physiologically-focused approach to train multi-modal artificial intelligence (AI) algorithms for medical applications. Specifically, the project aims to create a new deep neural network architecture that can accept and learn from multiple...
- This Project Grant award from 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 advanced deep learning algorithms to enhance the management of multiple myeloma (MM), a type of hematologic cancer. The $755,336 award, with a period of performance from August 1, 2025 to June 30, 2029, will focus on two key objectives: 1) Developing automated...
- This National Science Foundation (NSF) Project Grant award, under the Computer and Information Science and Engineering program (CFDA 47.070), provides $855,000 in funding to the Texas A&M Engineering Experiment Station (Tees) to develop a bimodal interpretable multi-instance medical image classification framework. The research aims to create a more scalable, interpretable, and robust artificial intelligence (AI) system to better analyze complex medical images, such as from multiple patient...
This $696,824 federal Project Grant award from 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), supports research at the University of North Carolina at Chapel Hill (UNC-CH) to develop robust and interpretable multi-modal AI/ML models for precision medicine. The project aims to address key challenges in integrating complex, heterogeneous biomedical data types, such as genomics, medical imaging, and clinical narratives, to enable a comprehensive understanding of diseases like cancer and Alzheimer's. The research seeks to advance precision medicine by creating innovative machine learning frameworks that can effectively synthesize diverse data, handle incomplete information, and provide interpretable insights into disease mechanisms. The award period runs from August 2025 through June 2029.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $696.8k | 8/8/25 |