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Machine Learning & AI for Healthcare 2019

Automating ML and AI to improve speed, accuracy of predictive models

3:58

(Sponsored) DataRobot describes how advances in auto-machine learning and predictive analytics are enabling healthcare enterprises to be AI-driven.

 

Talent is a critical element to get value from massive amounts of data

Amy Compton-Phillips, EVP and CCO at Providence St. Joseph Health, talks about her organization's chief medical analytics officer who is a physician and data scientist, so he is able to understand clinical context as well as data structure.
 

How blockchain and AI can work together for healthcare

Tej Anand, professor of practice at the University of Texas' McCombs School of Business, explains how the most promising use case for blockchain in healthcare is the elimination of "redundant work, rework and reconciliation."
 

Bundling predictive and descriptive analytics to create patient risk scores

Westchester Medical Center integrated data from the EHR using a machine learning algorithm to connect patients to the right sources of care, according to Simer Sodhi, the organization's director of data management & analytics.
 

How Cleveland Clinic harnesses machine learning for its pop health goals

Joseph Dorocak, manager of population health analytics at Cleveland Clinic, describes some of the staffing and process strategies the health system uses as it puts AI to work for two intertwined aims: better patient outcomes and financial return.