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Ganapati (Gans) Srinivasa, Co-Founder & CEO, Omics Data Automation
Abstract:
The amount and diversity of data generated in the care and treatment of cancer patients is ever increasing, resulting in large, heterogeneous and siloed Omics, Imaging and EHR / Phenotype/ Clinical Trial data sets. We will describe how the Omics Data Automation Framework stores, processes, and manages data from large, multimodal data sources for cancer patients to accelerate progress in basic science and clinical trials. In particular we will cover the details and techniques as applied in a case study of 300+ Prostate Cancer patients and the application of Deep Learning and Causal Modeling to learn from that data. Finally, we discuss future directions on how intelligent assistants/causal learning from federated systems can improve patient outcomes and reduce health care expenditures.
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