A team of researchers at the University of Florida will explore ways to increase trustworthiness and interpretability of artificial machine learning in healthcare under a new $1.2 million grant from the National Science Foundation. The team will also investigate ways to use AI to diagnose neurodegenerative diseases earlier.
The project will provide a paradigm shift for explainable AI, explaining how and why a machine learning model makes its prediction. Researchers hope to take a proof-based approach, “which probes all the hidden layers of a given model to identify critical layers and neurons involved in a prediction from a local point of view.” Researchers also plan to build a verification framework, where users can verify the model’s performance and explanations.
The UF research team is led by principal investigator My T. Thai, Ph.D., a professor in the Department of Computer & Information Science & Engineering, and co-principal investigators Ruogu Fang, Ph.D., an assistant professor in the J. Crayton Pruitt Family Department of Biomedical Engineering, and Adolfo Ramirez-Zamora, M.D., an associate professor in the Department of Neurology. UF is partnering with Carnegie Mellon University on the project.
Read the full story on the Herbert Wertheim College of Engineering website.