Interpreter of Maladies: Application of Machine Learning to Precision Oncology
In this webinar, Emory University’s Dr. Anant Madabhushi will share how radiomic and pathomic approaches (derived from machine learning tools) can help predict disease outcome, recurrence, progression, and therapy response in the context of cancer.
Such approaches can assist your work in:
- prostate cancer.
- brain cancer.
- rectal cancer.
- oropharyngeal cancer.
- lung cancer.
Dr. Madabhushi and his team have been developing computerized knowledge alignment, representation, and fusion tools for integrating and correlating heterogeneous biological data. Such machine learning tools are valuable for precision oncology.
Dr. Madabhushi is a professor at the Wallace H. Coulter Department of Biomedical Engineering at Georgia Institute of Technology and Emory University. He also serves as executive director at the Emory Empathetic Artificial Intelligence (AI) for Health Institute. His team applies AI, radiomics, computational pathology, medical image analysis, and computer vision to the diagnosis, prognosis, and prediction of treatment responses across diseases (including cancer).