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Machine Learning & AI for Healthcare 2019

How blockchain and AI can work together for healthcare

5:56

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."

 

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

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

How to operationalize AI, putting it to work for better care at lower cost

Machine learning is only a means to an end, helping organizations learn from data more quickly and intuitively, says Leonard D'Avolio, founder and CEO of Cyft.

 

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 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.