Embedded Files
Dr. Adam Alessio
Dr. Adam Alessio
Adam Alessio is a professor in the departments of Computational Mathematics, Science, and Engineering (CMSE), Biomedical Engineering (BME), and Radiology. He is currently serving as the Interim Chair of the Department of Biomedical Engineering His research is focused on non-invasive quantification of disease through advanced imaging algorithms and integrated data analysis.
Prior joining MSU, Dr. Alessio was a professor of Radiology at the University of Washington. He received his Ph.D. in Electrical Engineering at the University of Notre Dame and post-doctoral training in nuclear medicine physics at the University of Washington. He is the author of over 70 peer-reviewed publications, holds 6 patents, and has grant funding from the National Institutes of Health and the medical imaging industry to advance non-invasive cardiac and cancer imaging.
Title: Image-Driven Machine Learning for Diagnostic Healthcare
Abstract:
Medical diagnostics includes a wide range of complex tasks such as detecting and localizing disease, estimating risk, predicting outcomes, and determining efficacy of treatments. Data-driven methods have increasingly been applied to diverse medical decisions although the promise of AI in healthcare is largely unrealized despite the hype. This talk presents a survey of our lab's recent efforts applying data driven solutions for a) image generation from tomographic systems, b) rib fracture detection and localization in pediatric radiographs, and c) overcoming multimodal learning challenges in cancer detection. In other words, how are we going to take advantage of all this great data!
Report abuse