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2017 GTC San Jose

S7420 - Deep Learning of Cancer Images for Precision Medicine

Session Speakers
Session Description

We'll demonstrate a deep learning framework to predict survival of lung cancer patients by using convolutional networks to learn high-dimensional representations of tumor phenotypes from CT images and clinical parameters. We'll evaluate our framework from three independent cohorts with survival data, and show how the addition of clinical data improves performance. Furthermore, we'll describe how image noise can improve the robustness of our model to delineation errors and introduce the concept of priming, which helps improve performance when trained on one cohort and tested on another.


Additional Session Information
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Talk
AI in Healthcare Summit Deep Learning and AI Healthcare and Life Sciences Medical Imaging Video and Image Processing
Healthcare & Life Sciences Higher Education / Research
25 minutes
Session Schedule