Project Grant 2500836
- This $546,385 Project Grant from the National Science Foundation's (NSF) Computer and Information Science and Engineering program (CFDA 47.070) will support the development of a machine learning framework for training models across hospitals to address screening and treatment disparities in breast cancer. Specifically, the grant will fund research at Stanford University from September 2022 to August 2026 to create a fair federated representation learning algorithm and framework that can train...
- This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program grant, with the CFDA number 47.070, provides $203,981 in funding to Kean University to develop a weakly-supervised breast cancer detection system using active and weakly-supervised learning techniques applied to breast ultrasound imaging. The project aims to create a deep learning model that can effectively detect breast cancer in ultrasound images with minimal reliance on costly manual...
- This National Science Foundation Project Grant of $606,649 will support the development of an engineered cyber-physical system combining advanced biological models and artificial intelligence methods to enable precision medicine for cancer treatment. Awarded under the Computer and Information Science and Engineering program, the funding will be used by Brigham and Women's Hospital and its parent organization Partners Healthcare System from October 2022 to September 2025. Specifically, the...
- This 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), aims to improve the diagnostic accuracy and cost-effectiveness of breast cancer screening through the development of an AI system. The $672,087 grant, awarded on August 12, 2025, will fund a research project at New York University School of Medicine to build a...
- This Project Grant award of $275,956.00 from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program supports the development of an engineered cyber-physical system that combines advanced biological models with state-of-the-art artificial intelligence methods for predictive, automated screening of anti-cancer drugs and optimizing their dosing. The goal is to realize a precision medicine paradigm that can improve health outcomes and reduce treatment...
- The National Science Foundation (NSF) awarded a $131,290 Project Grant under the Computer and Information Science and Engineering (CISE) program to Clayton State University and Jarvis Christian University. The grant funds a collaborative research project to develop novel machine learning (ML) algorithms and Internet of Things (IoT) hardware for cancer detection, prediction, and treatment. The key objectives are to: 1) create ML-based software to detect, identify, and predict cancer cell growth...
- This $300,000 Project Grant awarded by the National Science Foundation (NSF) under the Integrative Activities (CFDA 47.083) program supports the development of an innovative, intelligent surgical probe for prostate cancer treatment. The project aims to create an edge artificial intelligence (AI) system-on-chip for bioimpedance analysis that can accurately distinguish cancerous from healthy tissue during prostate removal surgery. The novel technology being developed includes an adaptive filter to...
- 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...
- The National Cancer Institute awarded a $717,667 Project Grant titled "Artificial Intelligence Enabled Stroma-Weighted Automated Grading System to Improve Risk Stratification in Black Men" under the Cancer Detection and Diagnosis Research program (CFDA 93.394). The grant aims to develop an AI-enabled automated grading system that leverages multiphoton microscopy and second harmonic generation imaging to analyze prostate cancer tumor biology and improve risk stratification, particularly...
- This Project Grant from the National Science Foundation's Division of Information and Intelligent Systems, under the Computer and Information Science and Engineering program (CFDA 47.070), provides $300,000 to Arizona State University to develop a machine learning framework for training models across hospitals on electronic health records without sharing patient data. The framework aims to address fairness and mitigate biases by training representation learning algorithms jointly across multiple...
This $1,000,000 Project Grant was awarded on August 1, 2025 by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) federal grant program. The funding supports the development of a novel Artificial Intelligence (AI) and Machine Learning (ML) framework to reduce health outcome variability for breast cancer, particularly among Black women who experience disproportionately higher mortality rates. The key products and services to be delivered under this 4-year project include: Establishing a multi-omics data integration model to enhance breast cancer outcomes by leveraging a broader and more complete set of training data to improve the generalizability and capabilities of the ML models. Developing a multi-modal transfer learning framework that can effectively pre-train and fine-tune AI/ML models using limited clinical data to address the challenge of data scarcity in healthcare settings. The project is being led by the University of Nebraska Medical Center (UNMC), a prominent academic research institution with extensive expertise in medical research, public health studies, and innovative healthcare solutions. This effort aims to ultimately enhance the quality of health outcomes in breast cancer detection, diagnosis, prognosis, and treatment through the application of advanced AI and ML techniques.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $1.0m | 7/23/25 |