This $622,401 Project Grant award, funded by the National Institute on Aging (CFDA 93.866 - Aging Research), will support a multi-arm research project to elucidate the causal sequence of brain biomarker changes leading to Alzheimer's disease (AD) and identify modifiable lifestyle factors that could delay disease onset. The key research objectives include: Developing advanced deep learning models to predict amyloid load from readily available single-shell diffusion MRI data in symptomatic and...
This $2,365,042 Project Grant award from the National Institute on Aging's Aging Research Federal Grant Program (CFDA 93.866) supports a comprehensive research study to evaluate the biological underpinnings of Alzheimer's disease and related dementias (ADRD) across the U.S. and India. The study aims to leverage harmonized data on neurodegenerative biomarkers, cognitive outcomes, and other markers to assess the interplay between biological factors, social determinants, and ADRD risk. Key...
This federal Project Grant award from the National Institute on Aging (CFDA 93.866 Aging Research) provides $738,014 to Emory University to develop explainable and ethical artificial intelligence (AI) models for automated diagnosis and prognosis of Alzheimer's disease (AD). The award will leverage Emory's expertise in explainable AI, cerebrospinal fluid proteomics, and understanding the effects of race, social determinants of health, and comorbidities on AD pathophysiology. The goal is to create...
The National Institute on Aging (NIA), part of the Department of Health and Human Services National Institutes of Health, awarded a $3.37 million Project Grant to The University of Texas at Arlington to develop an individualized deep connectome framework for Alzheimer's disease and related dementias (ADRD) analysis. The three-year grant, awarded on August 18, 2022 under the NIA's Aging Research program (CFDA 93.866), will support research to discover and identify individualized...
This Project Grant award from the National Institute on Aging (CFDA 93.866 - Aging Research) will fund a comprehensive study to investigate multi-domain risk factors and prediction of Alzheimer's disease and related dementias (AD/ADRD) in a South Asian population in India. The $12.8M award to Emory University will support a 5-year research project focused on the following key objectives: Performing multimodal AD/ADRD phenotyping and genetic characterization of risk across the disease...
This Project Grant award, funded by the National Institute on Aging (CFDA 93.866 - Aging Research), aims to develop high-performing, fair, and interpretable large language models (LLMs) to detect Alzheimer's disease (AD) and its precursor stages, Mild Cognitive Impairment (MCI), from transcribed unstructured speech samples. The $300,506 award, effective from Aug 1, 2024 to May 31, 2028, will test the use of fair and explainable LLMs to identify early stages of the AD trajectory, focusing on...
The University of Southern California (USC) was awarded a $4,975,336 Project Grant from the National Institute on Aging (CFDA 93.866 - Aging Research) to develop advanced magnetic resonance imaging (MRI) techniques for mapping and quantifying cerebral small vessels as imaging biomarkers of vascular cognitive impairment and dementia (VCID). The project aims to optimize acquisition protocols and analysis pipelines for black-blood and arterial spin labeling MRI at 3 Tesla to comprehensively...
This $766,467 Project Grant award was provided by the National Institute on Aging (NIA) under the Aging Research Federal Grant Program (CFDA 93.866) to the Georgia State University Research Foundation Inc. The funding supports the development of flexible multivariate models that can jointly analyze multi-scale neuroimaging and genomic data to better understand Alzheimer's disease and related dementias (ADRD). The proposed models aim to address key limitations of existing multivariate data fusion...
This National Institutes of Health (NIH) National Institute on Aging (CFDA 93.866 Aging Research) Project Grant award of $614,424 to the University of Washington is for a research project titled "Illuminating Early Microglial Dysfunction in Alzheimer's Disease Through Integration of Explainable AI and iPSC Models." The project aims to use novel AI techniques and human-derived induced pluripotent stem cell (iPSC) models to better define how microglia, the brain's immune cells,...
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...
The National Institute on Aging (NIA) awarded a $661,016 Project Grant (CFDA 93.866 - Aging Research) to the University of Southern California (USC) to develop a federated deep learning platform called "FEDERATE AD" that will accelerate Alzheimer's disease (AD) research. The key products and services to be delivered under this award include:
Developing an international AI alliance to analyze AD biobanks from the U.S., India, Japan, and Europe, comprising over 100,000 MRI and PET scans, to (a) diagnose and subtype dementia using deep learning, (b) infer brain amyloid and tau burden from clinical data and neuroimaging, and (c) predict clinical decline from mild impairment to AD.
Applying federated deep learning and data harmonization techniques to yield site-invariant predictive models that can generalize across diverse ancestries, reducing bias and enhancing diversity in AD research.
Integrating the project's AI innovations and toolkit with other NIA-funded initiatives in machine learning and phenotypic harmonization to maximize the impact on the AD research field.
The award period runs from September 2024 through August 2029. The project includes sub-awards to the University of Texas Health Science Center at Houston and the Regents of the University of California at Riverside to collaborate on specific components of the federated deep learning platform development.