Precision oncology requires molecular and genetic testing of tumor tissue. For many tests, universal implementation in clinical practice is limited because these biomarkers are costly, require significant expertise and are limited by tissue availability. However, virtually every cancer patient gets a biopsy as part of the diagnostic workup and this tissue is routinely stained with hematoxylin and eosin (H&E). Recently, we and others have demonstrated that deep learning can infer tumor genotype, prognosis and treatment response directly from routine H&E histology images. This talk will summarize the state of the art of deep learning in oncology, demonstrate emerging use cases and discuss the clinical implications of these novel biomarkers.
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- Speaker: Prof Jakob Kather is a physician/scientist and assistant professor at RWTH Aachen University (Germany) with additional affiliations at the NCT Heidelberg (Germany) and the University of Leeds (UK).
- Monday 04 October 2021, 09:30-10:30
- Venue: ZOOM (live).
- Series: Seminars on Quantitative Biology @ CRUK Cambridge Institute ; organiser: Tania Smith.