Presented By O’Reilly and Cloudera
Make Data Work
March 5–6, 2018: Training
March 6–8, 2018: Tutorials & Conference
San Jose, CA

Philip Lavori
Professor of Biomedical Data Science, Stanford University

Math PhD 1974 Cornell, on faculty at MIT, Harvard, Brown and Stanford. Specialist in adaptive designs for clinical trials, use of observational data for causal effects of treatment, trials embedded in clinical practice.

Sessions

5:10pm–5:50pm Wednesday, March 7, 2018
Distributed clinical models: Inference without sharing patient data
Big data and data science in the cloud, Data science and machine learning, Platform security and cybersecurity
 Location: LL20 D
Balasubramanian Narasimhan (Stanford University), John-Mark Agosta (Microsoft), Philip Lavori (Stanford University)
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Clinical collaboration benefits from pooling data to train models from large datasets, but it's hampered by concerns about sharing data. Balasubramanian Narasimhan, John-Mark Agosta, and Philip Lavori outline a privacy-preserving alternative that creates statistical models equivalent to one from the entire dataset. Read more.