Project Grant 2500341
- This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Program Project Grant award of $324,160 supports the development of novel machine learning and natural language processing algorithms to automatically extract personal risk factors from electronic health records for early prediction of Alzheimer's disease and related dementias (ADRD). The project aims to integrate these personal risk factors, such as education, employment, and lifestyle, with...
- This federal Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CFDA 47.070) program provides $150,000.00 to Saint Vincent College to develop algorithms, software, and systems that can train machine learning models on electronic health records (EHRs) for accurate and early prediction of Alzheimer's disease and related dementias (ADRD). The project aims to create computational tools that can automatically extract personal risk factors,...
- This Project Grant award from the National Science Foundation (CFDA 47.070 - Computer and Information Science and Engineering) provides $150,000.00 to The University of Iowa to advance national health and promote science and technology development. The project aims to develop a computational platform using novel machine learning and natural language processing techniques to automatically extract personal risk factors from electronic health records and leverage them for accurate and early...
- This four-year $1.15 million Project Grant from the National Science Foundation's Computer and Information Science and Engineering program (CFDA 47.070) supports research at the University of Michigan to develop techniques for learning from longitudinal observational clinical data in the presence of noise and confounding to tackle progressive diseases. The University will create shareable electronic health record-based definitions of mild cognitive impairment and Alzheimer's disease, and develop...
- This National Science Foundation (NSF) Project Grant award to Wake Forest University, under the Computer and Information Science and Engineering (CFDA 47.070) program, aims to develop a "Neuron Twin" computational system that simulates the human brain to improve understanding and predictions related to Alzheimer's disease. The $501,329 five-year project will leverage deep learning and multiscale modeling to jointly analyze multimodal data, including genetic, neuroimaging, and...
- This $287,118 Project Grant was awarded on September 1, 2023 by the National Institute on Aging (NIA) under the Aging Research (CFDA 93.866) grant program. The grant will fund the development of techniques to use deep transfer learning and multimodal data, including brain MRIs, genetic information, and cognitive tests, to enable the early detection and forecasting of Alzheimer's disease progression. The University of Massachusetts (UMass), as the prime awardee, will create an end-to-end...
- This Project Grant award of $129,330 from the National Institute on Aging (NIA), under the Aging Research federal grant program (CFDA 93.866), supports research at the Massachusetts General Hospital (MGH) to address the critical unmet need for early and accurate detection of Alzheimer's disease and related dementias (ADRD). The key products and services to be delivered under this award include: 1) deploying a multi-modal information framework that leverages decades-long in vivo and digital...
- This $224,994 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CFDA 47.070) program supports the development of a new framework for digital twin modeling of Alzheimer's disease (AD). The University of Illinois project aims to combine clinical data, biomedical research, and advanced computational methods to create personalized digital twins that can predict disease progression and evaluate treatment options. The digital twin models...
- This Project Grant award from the National Institute on Aging (CFDA 93.866 - Aging Research) for $791,086 aims to develop computational models that can predict the presence of non-Alzheimer's disease neuropathological changes, such as Lewy body disease, TDP-43 proteinopathy, and cerebral amyloid angiopathy, in individuals with Alzheimer's disease neuropathological changes. The project will leverage data from autopsy-confirmed datasets, in vivo neuroimaging, and clinical assessments to build...
- This $1,183,690 Project Grant awarded by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program funds research to develop personalized artificial intelligence (AI) models that can predict repeat adverse health events like substance use and stress-related blood pressure spikes using data from wearable devices like Fitbit and Apple Watch. The key innovation is training these models to learn from each individual's unique biosignal data patterns,...
This Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program provides $375,840 to develop advanced machine learning models and algorithms that can accurately and early predict the onset of Alzheimer's disease and related dementias (ADRD) using electronic health record data. The project aims to extract personal risk factors for ADRD, such as education, employment, and lifestyle, from unstructured clinical notes and leverage them to enhance the predictive capabilities of the machine learning models. This research will significantly improve the timeliness and accuracy of ADRD predictions, with potential applications to other neurological disorders. The award is granted to the Rector & Visitors of the University of Virginia, a prominent public research university, and will be conducted from October 1, 2025 to September 30, 2029.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $375.8k | 8/4/25 |