This National Science Foundation (NSF) Project Grant award, under the Computer and Information Science and Engineering program (CFDA 47.070), provides $855,000 in funding to the Texas A&M Engineering Experiment Station (Tees) to develop a bimodal interpretable multi-instance medical image classification framework. The research aims to create a more scalable, interpretable, and robust artificial intelligence (AI) system to better analyze complex medical images, such as from multiple patient scans, and provide trustworthy diagnostic tools to medical professionals. The project will leverage a large collection of medical images and doctors' notes to tackle challenges in dealing with rare diseases and providing explanations that are easily understood. The research team plans to disseminate their findings through publications, open-source software, training materials, and outreach initiatives. Subawards are planned as part of this 4-year award, which runs from September 1, 2023 through August 31, 2027.
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