Join us in discovering how artificial intelligence can aid oncologists and pathologists working in the gastrointestinal field. This webinar showcases an AI model, developed by the Mayo Clinic and Aiforia, that identifies important histological features of colorectal cancer and provides a recurrence prediction estimate useful for treatment decisions.
After the webinar, you will understand:
- The current state of colorectal cancer pathology and pathologic features that guide oncologic decision-making.
- How an AI-integrated risk scheme using available, inexpensive hematoxylin and eosin-stained slides can improve risk assessment for cancer patients.
When leveraged, there is tremendous morphologic heterogeneity in colorectal carcinoma that can predict prognosis, underlying molecular alterations, and response to specific therapies. QuantCRC, a deep learning segmentation algorithm harnesses quantitative data from digitized hematoxylin and eosin-stained slides to improve the prediction of tumor recurrence using the Aiforia® Platform. The AI model identifies clinically relevant prognostic risk groups, providing a powerful adjunct to routine pathologic reporting of colorectal cancer.
Watch the webinar to hear more about this exciting use case and learn how prognostic AI models are revolutionizing the future of pathology image analysis.
