Artificial Intelligence and Computational Imaging: Opportunities for Precision Medicine
In this webinar, University of Wisconsin-Madison’s Dr. Tiwari shares how she and her laboratory have created machine learning (ML) techniques to better understand the basic biology of tumors through non-invasive imaging, histopathology, and omics data.
- Discover how she and her team use this research to predict disease outcome, recurrence, progression, and therapy response (with a particular emphasis on brain tumors).
- Learn about ongoing efforts to design new image-based features for evaluating post-treatment outcomes and forecasting chemo-radiation treatment responses.
- Hear about the clinical implications of the ML techniques (in terms of translation).
The NCI Emerging Technologies Seminar Series highlights novel technologies being supported through NCI awards that could transform cancer research and clinical care.
Dr. Tiwari is a visiting associate professor in the radiology and biomedical engineering departments at the University of Wisconsin-Madison. She is also an assistant professor of biomedical engineering and the director of the Brain Image Computing Laboratory at Case Western Reserve University.
Upcoming Events
- Predicting Patients’ Response to Immunotherapy from Tumor Histopathology and Blood: Computational Science in Immuno-oncologyJuly 08, 2025Assessing the Tumor Microenvironment with Systems Immunology: Computational Science in Immuno-oncologyAugust 21, 2025Data Jamboree: Enhancing Childhood Cancer Data Sharing and UtilitySeptember 29, 2025 - September 30, 2025NCI Office of Data Sharing’s Annual Data Sharing Symposium 2025: How Data Advances the Impact of Cancer ResearchSeptember 30, 2025 - October 01, 2025Childhood Cancer Data Initiative (CCDI) Symposium 2025October 06, 2025 - October 07, 2025