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SITC 2022 | Radiomics, pathomics, AI for predicting + monitoring treatment response to cancer therapies

Anant Madabhushi, PhD, Emory University School of Medicine, Atlanta, GA, discusses radiomics, pathomics, AI for predicting and monitoring treatment response for cancer therapies with validation on clinical trial datasets. AI tools with routinely acquired data, such as hematoxylin and eosin (H&E) images, biopsies and CT scans, is used to be able to find patterns that are associated with clinically relevant outcomes and treatment response for cancer therapies. There is a major unmet clinical need to be able to predict in advance which patients will respond well to certain therapies. A variety of patterns have been identified from data collected that allow for predictions to be made on patient response. This interview took place at the 37th Annual Meeting of the Society for Immunotherapy in Cancer (SITC 2022) in Boston, MA.

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