Identifying Cancer Risk Early Using AI on Longitudinal Clinical Records
Chris Sander, Professor in Residence of Cell Biology, Systems Biology, Harvard Medical School and Ludwig Center at Harvard
When: Thursday 6 June, 12:30–14:00 including lunch
Where: Early Cancer Institute, Adrian Way, Cambridge Biomedical Campus, Cambridge, CB2 0XZ
Lunch is provided from 12.30, the talk will begin at 1pm followed by a Q&A. Please ensure you arrive promptly.
Speaker Biography:
Chris Sander is an internationally recognized expert in computational and systems biology, with recent focus on to the use of artificial intelligence in biomedicine. He has extensive experience in cancer genomics, was a leader in The Cancer Genome Atlas (TCGA) project. His group created the widely used cBioPortal for Cancer Genomics. His current research includes: (1) deriving AI-enabled quantitatively predictive network models from high-throughput molecular profiling (Cellbox); (2) rendering human biological knowledge computable and accessible, as an aid to biomedical discovery (cBioPortal, Pathway Commons); (3) using evolutionary constraints derived from rich sequence information to predict previously unknown 3D structures of biomolecules and to elucidate protein function (EVcouplings) and (4) using artificial intelligence methods applied to trajectories of real-world clinical records (EHRs) to develop surveillance programs for patients at high risk for agressive cancers (CancerRiskNet).
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