In this free webinar, learn about the current state of colorectal pathology and pathologic features that guide oncologic decision-making. Gain insights into improving risk assessments for cancer patients with an AI-integrated scheme and digital pathology. The featured speakers will discuss how the AI model can improve risk stratification to help guide treatment and follow-up.

TORONTO, May 30, 2024 /PRNewswire-PRWeb/ — Discover an informative webinar on how artificial intelligence (AI) can aid oncologists and pathologists working in the gastrointestinal field.

In this webinar, the speakers will focus on an AI model that identifies important histological features of colorectal cancer (CRC) and provides a recurrence prediction estimate that can be useful for making treatment decisions.

There is tremendous morphologic heterogeneity in colorectal carcinoma, which can be helpful for predicting prognosis, underlying molecular alterations and determining the response to specific therapies. QuantCRC, a deep learning segmentation algorithm, harnesses quantitative data from digitized hematoxylin and eosin (H&E)-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 CRC. By attending this webinar, the attendees will gain insights into:

• Current state of CRC pathology and pathologic features that guide oncologic decision-making
• How an AI-integrated risk scheme using available, inexpensive (H&E)-stained slides can improve risk assessment for cancer patients

Register for this webinar today to learn about the exciting case of AI in pathology and how prognostic AI models are revolutionizing the future of pathology image analysis.

Join Dr. Rish K. Pai, Pathologist, Mayo Clinic; and Thomas Westerling-Bui, Chief Commercial Officer, Aiforia Inc., for the live webinar on Thursday, June 13, 2024, at 11am EDT (4pm BST/UK).

For more information, or to register for this event, visit Using Prognostic AI Models in Pathology: Case Colorectal Cancer.

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