Project Grant 2318573
- 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 National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Project Grant award (CFDA 47.070) of $195,000 will fund the development of a weakly-supervised breast cancer detection system using active and weakly-supervised learning techniques to improve breast cancer diagnosis from ultrasound images. The project aims to create a deep learning model that can detect breast cancer effectively with minimal annotations, addressing the challenges of noisy, low-contrast...
- The National Science Foundation (NSF) awarded a $199,792 Computer and Information Science and Engineering (CISE) program grant to the University of Miami to develop novel methodologies for detecting data shifts in artificial intelligence/machine learning-enabled software as a medical device (AI/ML-SAMD) in medical cyber-physical systems. The project aims to create a framework that allows SAMDs to adapt through real-world learning, enhancing their safety and effectiveness in detecting lung cancer...
- This Project Grant award from the National Science Foundation Division of Information and Intelligent Systems provides $350,000 in funding to the University of Illinois from September 2022 through August 2026. The award supports research under the Computer and Information Science and Engineering federal grant program (CFDA 47.070). Specifically, the University of Illinois will develop a machine learning framework for training models across hospitals to support precision population health and...
- 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...
- The University of Nebraska Medical Center (UNMC) received a $1.0 million Project Grant awarded August 1, 2025, through the National Science Foundation's Computer and Information Science and Engineering (CISE) program (CFDA 47.070). The four-year project, concluding July 31, 2029, will develop a novel artificial intelligence and machine learning framework to reduce health outcome variability in breast cancer detection, diagnosis, prognosis, and treatment. The research specifically addresses...
- This National Science Foundation (NSF) Division of Mathematical Sciences grant award of $278,537 to Northeastern Illinois University aims to develop a novel, equitable machine learning methodology to predict colorectal cancer, lung cancer, and postpartum health outcomes. By leveraging electronic medical records and socio-environmental data from Chicago, the project will test and compare the performance of the "Triple Discriminant Scoring" approach against existing techniques like...
- This two-year, $156,911 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), will fund research applying graph neural networks, self-supervised learning, and meta learning techniques to cancer multi-omics data and driver discovery. Specifically, the awardee, Oakland University, will construct a graph neural network model incorporating biological domain knowledge to...
- 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...
- This $600,000 Project Grant awarded by the National Science Foundation (NSF) Division of Computing and Communication Foundations will fund the development of an innovative aerial imaging system that incorporates state-of-the-art artificial intelligence (AI) for real-time data processing and analysis. The project, titled "CISE-MSI:DP:REAL-TIME AERIAL IMAGING WITH EDGE AI," is a collaboration between students and faculty at Norfolk State University (NSU), a minority-serving institution...
COLLABORATIVE RESEARCH: CISE-MSI: RCBP-RF: CNS: ESD4CDAT - EFFICIENT SYSTEM DESIGN FOR CANCER DETECTION AND TREATMENT -THE APPLICATIONS OF MACHINE LEARNING (ML) BECOME MORE POPULAR FOR SOLVING REAL LIFE PROBLEMS NOT ONLY IN HEALTHCARE AND MEDICINES BUT ALSO IN OTHER FIELDS. ML PUSHES INVESTIGATORS FROM DIFFERENT FIELDS TO CONDUCT INTERDISCIPLINARY RESEARCH AND OBTAIN NEW DISCOVERY. THERE ARE MUTUALLY GROWING INTERESTS AMONG TEAM OF RESEARCHERS AT TWO INSTITUTIONS IN CONDUCTING RESEARCH ON THE APPLICATIONS OF ML AND INTERNET OF THINGS (IOT) FOR CANCER DETECTIONS, PREDICTIONS, AND TREATMENTS AT JARVIS CHRISTIAN UNIVERSITY (JCU) (FORMERLY JARVIS CHRISTIAN COLLEGE (JCC)) AND CLAYTON STATE UNIVERSITY (CSU). TO REALIZE THE INTERESTS OF THE INVESTIGATORS FROM BOTH UNIVERSITIES, A COLLABORATIVE RESEARCH PROJECT IS ESTABLISHED. THE PRIMARY GOAL OF THE PROJECT IS TO CATALYZE COLLABORATIONS AND EXPLORE NEW RESEARCH DIRECTIONS IN THE APPLICATIONS OF ML AND IOT FOR CANCER DETECTIONS, PREDICTIONS, AND TREATMENTS. TO SUPPORT THE ADVANCEMENT OF THE GOAL AND BENEFIT THE TEAM, THE PROJECT AIMS TO 1) DEVELOP NOVEL ML BASED ALGORITHMS TO BUILD SOFTWARE TO DETECT, IDENTIFY, AND PREDICT CANCER CELL GROWTHS AND TREATMENTS,? 2) INFUSE NOVEL ML ALGORITHMS WITH THE INEXPENSIVE IOT HARDWARE TO ENABLE DATA COLLECTION FOR THE CANCER RESEARCH, 3) DEVELOP SMART CAMERA BASED APPS FOR VISUAL SKIN CANCER DATA COLLECTIONS AND ANALYSIS, AND 4) OFFER UNDERGRADUATE AND GRADUATE COURSE PROJECTS OR THESES FOR THE TWO COLLABORATIVE INSTITUTIONS TO CONDUCT RESEARCH AND TRAINING IN APPLIED ML AND IOT FOR MEDICAL IMAGING AND CANCER TREATMENTS. THE MAJOR OUTCOMES OF THE PROJECT ARE 1) COLLABORATION AMONG STUDENTS AND FACULTY OF AN HBCU WITH A PREDOMINANTLY MINORITY SERVING INSTITUTE, 2) RESEARCH DATA COLLECTIONS AND ANALYSIS FOR CANCER DIAGNOSIS, PREDICTION, AND TREATMENT, 3) CURRICULUM ADVANCEMENTS AT UNDERGRADUATE AND GRADUATE LEVELS IN THE AREAS OF SOFTWARE DESIGN FOR ML AND IOT APPLICATIONS, AND 4) BUILD STRONGER FOUNDATIONS OF CONTINUING FUTURE COLLABORATIVE RESEARCH AND EDUCATION BETWEEN THE TWO INSTITUTIONS VIA CISE-MSI CORE FUNDING GRANTS. THIS AWARD WAS FUNDED IN PART BY THE HISTORICALLY BLACK COLLEGES AND UNIVERSITY EXCELLENCE IN RESEARCH (HBCU-EIR) AND THE CISE MINORITY SERVING INSTITUTIONS (CISE MSI) RESEARCH EXPANSION PROGRAMS. THIS AWARD REFLECTS NSF'S STATUTORY MISSION AND HAS BEEN DEEMED WORTHY OF SUPPORT THROUGH EVALUATION USING THE FOUNDATION'S INTELLECTUAL MERIT AND BROADER IMPACTS REVIEW CRITERIA.- SUBAWARDS ARE NOT PLANNED FOR THIS AWARD.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $2.2k | 9/7/23 |