This webinar was presented at the 2020 CGC (Cancer Genomics Consortium) Virtual Annual Meeting.
DNA methylation technology using AI classifiers is challenging the status quo approach to classifying complex solid tumors. New applications for predictive risk modeling are emerging that have the potential to provide better prognostic information and improve outcomes.
This webinar begins with an overview on the integration of novel methylation-based machine learning algorithms to improve accuracy of brain tumor histopathological diagnosis. A special focus on methylation profiling’s impact to patient management is provided.
The webinar discussion shifts to reviewing the development and validation of an individualized predictor of 5-year recurrence risk in meningioma. This innovative new approach combines DNA methylation signatures with prognostic clinical factors to more reliably predict outcomes.
Please join Dr. Gelareh Zadeh and Dr. Farshad Nassiri, as they highlight their transformative work using DNA Methylation technology and methylome-based predictors at the University of Toronto.
Gelareh Zadeh, MD, PhD, Head, Division of Neurosurgery and Medical Director, Krembil Neuroscience, Senior Scientist, University Health Network and University of Toronto; President of SNO (Society of Neurooncology) with Farshard Nassiri, MD, Neurosurgery Resident, University of Toronto
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