UF Researchers Seek To Build Confidence Into AI for Healthcare Under NSF Grant (Powering the New Engineer)

UF Researchers Seek To Build Confidence Into AI for Healthcare Under NSF Grant

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.

“AI has become an essential part of the modern digital era, especially toward enhancing healthcare systems. Unfortunately, when AI makes headlines, all too often it is because of problems with biases, inexplicability and untrustworthiness,” said Dr. Thai, the associate director of the Warren B. Nelms Institute for the Connected World. “Now it is time for us to take a deeper look to make AI-based decisions more explainable, transparent and reliable. I am excited about this opportunity to lead a multidisciplinary team to conduct such fascinating research.”

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