Project Grant R43AG097131
- This $1,012,879 Project Grant was awarded by the National Institute on Aging (CFDA 93.866 - Aging Research) to New York University (NYU) to develop three novel statistical machine learning methods for Alzheimer's disease (AD) research using multi-view imaging, genomic, and clinical data. The specific aims include: 1) developing a multi-view data decomposition method to construct brain and genomic networks across AD statuses, 2) developing an optimal false discovery rate control method to...
- This federal Project Grant award of $3,080,520.00 from the National Institute on Aging (CFDA 93.866 - Aging Research) supports research to develop novel biomarkers for the early detection of Alzheimer's disease and related dementias (ADRD) using resting-state functional magnetic resonance imaging (rs-fMRI) data and machine learning. The research aims to address limitations of current ADRD biomarkers by leveraging the dynamics of functional connectivity networks and accounting for heterogeneity...
- This SBIR Phase I Project Grant award from the National Science Foundation's (NSF) Technology, Innovation, and Partnerships (CFDA 47.084) program provides $303,089 to Bioimaginix LLC at West Virginia University Research Corporation. The goal is to develop an AI/machine learning-based algorithm that can distinguish between Alzheimer's disease (AD) and mild cognitive impairment (MCI) using MRI brain scans. The technology aims to enable early detection of AD, particularly at the MCI stage, to...
- This federal Project Grant award of $817,357 from the National Institute on Aging (CFDA 93.866 - Aging Research) aims to harness novel machine learning approaches for behavioral segmentation and brain signal integration in humanized models of Alzheimer's disease. The key products and services to be delivered under this grant include: Further validation of the grantee's "Variational Animal Motion Embedding (VAME)" machine learning platform for comprehensive behavioral phenotyping of...
- This $375,840 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports the development of advanced machine learning models to enable accurate and early prediction of Alzheimer's disease and related dementias (ADRD). The project, led by the University of Virginia, will leverage novel natural language processing techniques to automatically extract personal risk factors for ADRD from electronic health...
- This $500,000 Project Grant was awarded on September 15, 2024 by the National Institute on Aging (CFDA 93.866 Aging Research program) to Neucyte Inc., a minority-owned small business specializing in advanced biomedical research and development. The funding will support the development of a miniaturized "mini-brain" microphysiological system (MPS) platform using Alzheimer's disease (AD) patient-derived cells. The goal is to create a scalable, reproducible in vitro brain model that can...
- 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 federal Project Grant award of $150,000.00, funded by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070), aims to develop advanced machine learning models and algorithms for the early prediction of Alzheimer's Disease and Related Dementias (ADRD) using electronic health record (EHR) data. The research project, led by the University of Iowa, will leverage natural language processing techniques to automatically extract...
- This federal Project Grant award of $3,188,901.00 from the National Institute on Aging (CFDA 93.866 - Aging Research) aims to better understand the relationships between in-vivo biomarkers for amyloid, tau, and neurodegeneration (ATN), neuropsychiatric symptoms, vascular risk factors, and genetic risks in Alzheimer's disease. The study will leverage data from large research cohorts like the Alzheimer's Disease Neuroimaging Initiative to develop and optimize machine learning models that can...
- This $786,440 Project Grant award from the National Institute on Aging's (NIA) Aging Research Federal Grant Program (CFDA 93.866) supports research at Emory University to evaluate the Visuospatial Memory Eye-Tracking Test (VISMET) as a digital biomarker for detecting preclinical Alzheimer's disease (AD). The project aims to replicate prior findings that VISMET performance predicts global cognition, determine if VISMET can detect preclinical AD and predict longitudinal cognitive decline, and...
This federal Project Grant award of $495,731.00, awarded on September 20, 2025 by the National Institute on Aging (CFDA 93.866 Aging Research program), supports the evaluation of Viewmind's ability to detect beta-amyloid and tau burden consistent with Alzheimer's disease in persons with mild cognitive impairment (MCI) using machine learning, virtual reality, and eye-tracking technology. The project aims to develop a non-invasive, cost-effective, and rapid diagnostic tool that can accurately identify MCI due to Alzheimer's disease at its earliest stages and measure functional impacts across cognitive domains, enabling timely interventions and the ability to monitor their effects. The award recipient is Viewmind Inc., a digital health and AI company providing clinically validated solutions for precision diagnostics of neurocognitive disorders.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $495.7k | 9/18/25 |