Science Café Cleveland—“Artificial Intelligence and Precision Medicine: Addressing Patient and Financial Toxicity on Account of Over-Treatment”

Traditional medical biology generally looks at only a few aspects of an organism at a time, attempting to molecularly dissect diseases and study them part-by-part, with the hope that the sum of the knowledge of the parts will help explain the operation of the whole. However, this approach has rarely been a successful strategy to understand the causes and cures for complex diseases.

The motivation for a systems-based approach to understanding disease is to understand how large numbers of interrelated health variables result in the emergence of definable body states (AKA “phenotypes”). The Center for Computational Imaging and Personalized Diagnostics (CCIPD) at Case Western Reserve University has been developing computationally guided imaging and machine learning tools that are able to characterize disease appearance and behavior on radiographic (AKA “radiomics”) and digitized pathology (AKA “pathomics”) images.

At the next Science Café Cleveland event, Anant Madabhushi, the Donnell Institute Professor of Biomedical Engineering at the Case School of Engineering and professor of pathology at the School of Medicine, will discuss how these radiomic and pathomic approaches can be applied to predicting disease outcome, recurrence, progression, and response to therapy in the context of prostate, brain, rectal, oropharyngeal, and lung cancers. 

Additionally, he will discuss his recent work looking at the use of pathomics in the context of racial health disparities, and the creation of more precise and tailored prognostic and response prediction models.

This virtual conversation, hosted by Sigma Xi: The Scientific Research Honor Society and titled “Artificial Intelligence and Precision Medicine: Addressing Patient and Financial Toxicity on Account of Over-Treatment,” Monday, Feb. 8, at 7 p.m. Get the Zoom information via the Facebook event page.