About this Class

Dr. Anant Madabhushi and his team have been developing computerized knowledge alignment, representation, and fusion tools for integrating and correlating heterogeneous biological data spanning different spatial and temporal scales, modalities, and functionalities. These tools include computerized feature analysis methods for extracting subvisual attributes for characterizing disease appearance and behavior on radiographic (radiomics) and digitized pathology images (pathomics). Over the last dozen years, there has been substantial progress in developing new radiomic and pathomic approaches for capturing intra-tumoral heterogeneity and modeling tumor appearance. Specifically, Dr. Madabhushi 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.

NIH registrants who attend more than 45 minutes of the webinar are eligible for 1 ESA credit and a certificate of completion. The certificate will be sent to the email address provided at the time of registration. If you have questions about ESA accreditation for Infectious Agents and Cancer Epidemiology Research webinars, please email iaandcancer@mail.nih.gov.