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Friday, October 6 • 3:15pm - 4:00pm
Two Use-cases and a Summary: AI in Health for Diabetes and Communicable Disease

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A surge in health care data, including electronic health records and medical sensor data, is providing new opportunities to uncover data-driven insights and patterns of disease using machine learning techniques. Sanjay Joshi and Karen Hayrapetyan will present a summary of AI in Health and two separate use cases that could reduce cost and increase care.

The first use case is predicting diabetes hospital readmissions using H2O's gradient boosted trees using the diabetes dataset from 130 US hospitals For the second use case we present a geo-spatial forecasting system for seasonal communicable disease that has the potential to aid public health planning and help reduce the impact of outbreaks, specifically for time-series forecasts of Influenza-like illness (ILI) encounters at county and zip-code levels with increased performance compared to conventional systems that predict ILI incidents at isolated spatial scales

avatar for Karen Hayrapetyan

Karen Hayrapetyan

Senior Data Scientist, H2O.ai
Karen Hayrapetyan is a senior data scientist at H2O.ai. Karen works with H2O.ai customers to derive substantive business value from machine learning technologies. Prior to joining H2o.ai, he spent three years at startups working on growth and analytics problems. He holds a Ph.D. in... Read More →
avatar for Sanjay Joshi

Sanjay Joshi

Chief of Technology, Healthcare and Life Sciences, H2O.ai
Sanjay Joshi is the Chief of Technology, Healthcare and Life Sciences at H2O.ai. Based in Seattle, Sanjay's 25+ year career has spanned the entire gamut of life-sciences and healthcare from clinical and biotechnology research to healthcare informatics to medical devices to IT infrastructures... Read More →


Friday October 6, 2017 3:15pm - 4:00pm CDT
Room 1, 2 & 3 Optum, 13625 Technology Drive, Eden Prairie, MN, United States