Over $31 million was allocated to researchers at UTHealth Houston’s McWilliams School of Biomedical Informatics on November 20, 2023, for 16 projects dedicated to advancing artificial intelligence (AI) in healthcare.
Among the grants are 14 innovative awards and two additional recognitions. The National Institute on Aging (NIA), a branch of the National Institutes of Health (NIH), granted five of these awards, totaling over $19 million.
The initial project aims to assess the efficacy of Alzheimer’s disease treatment. Researchers involved in the study noted significant knowledge gaps regarding non-responsive individuals to these treatments.
By developing machine learning models to identify patient subgroups with varying treatment responses, the project aims to bridge these gaps effectively.
The subsequent project aims to establish the “Alzheimer’s Disease Clinical Trial Simulation” platform, which will serve as a user-friendly, reusable, and standardized tool for designing and simulating trials related to the disease.
Dr. Cui Tao, the principal investigator of the project and the Dr. Doris L. Ross Professor at the Department of Health Data Science and Artificial Intelligence, emphasized the urgent need to address challenges in Alzheimer’s disease and related research. The integration of real-world data and clinical trial simulation is seen as a groundbreaking approach to advancing understanding and potentially discovering more effective treatments.
The project receiving the highest funding, AIM-AI, with a total budget of $6.4 million, aims to develop a comprehensive genetic catalog of Alzheimer’s disease. This “genetic map” could integrate biological insights with other modalities for causal and drug discovery research.
Another project highlighted in the press release focuses on establishing a robust informatics framework that incorporates mathematical identification and ontology information to harmonize electronic health records.
Furthermore, the NIA award will contribute to an ongoing project utilizing defined neuroimaging data to benchmark AI algorithms.
The National Library of Medicine (NLM) at the NIH awarded three new grants, with one being transferred to the institution.
One of the supported projects concentrates on enhancing training techniques for foundational scientific models, potentially improving clinical prediction models and applications in deep learning.
Another project aims to integrate genetic data sharing with institutional review boards to facilitate transparent evaluations for clinical trials.
Moreover, ongoing research seeks to develop deep learning methods for translating genomic data into formats suitable for genetic research.
A transferred grant worth $1.9 million will support an initiative focused on advancing clinical research software using electronic health record (EHR) data through enhanced demographic discovery and identification.
Additionally, instructors at the NIH received two awards from the National Human Genome Research Institute. One award supports the continuation of work on the “RaPID” algorithm, which analyzes biological relationships and identifies genetic divisions among individuals based on distance.
Another project aims to increase awareness of rare conditions among healthcare providers through an analytics model designed to expedite problem analysis.
Furthermore, five additional NIH grants were awarded, including the NIH’s Artificial Intelligence/Machine Learning Consortium to Advance Health Equity and Researcher Diversity (AIM-AHEAD) Program.
One of these projects will investigate the impact of donor-recipient body type mismatches in organ transplants and develop interventions to reduce health disparities using AI and machine learning.
Another project aims to collaborate with experts from Tuskegee University to enhance data management, implement health AI, and promote health equity for minority populations.
The second additional NIH grant supports a project focusing on personalized therapy for the lymphatic system and advancing cancer treatment research.
Moreover, a sequential informatics program accessible to the broader medical community will be developed as part of the third project.
The final award, the “Infrastructure Innovation for Biological Research” grant from the National Science Foundation, will be utilized to develop machine learning resources for advancing research on cell growth.
Dr. Jiajie Zhang, professor and Glassell Family Foundation Distinguished Chair in Informatics Excellence at McWilliams School of Biomedical Informatics, emphasized the crucial role these grants play in furthering the impact of technology in healthcare.
“Medical AI remains the central theme of the recently awarded grants,” Dr. Zhang stated. He highlighted the ongoing Cognitive Revolution driven by AI and emphasized the significance of these advancements and research studies in the current landscape.
