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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.

 

AI is having real-world impact at Cleveland Clinic, Duke and beyond

Todd Schlesinger, VP of business development at Jvion, says AI has already moved beyond its status as a novel technology with exciting potential use cases, to one that is already helping solve real-world challenges and improving patient outcomes.
 

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."
 

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.
 

AI in healthcare has come a long way, and quickly - where's it going next?

Badrul Husain, CEO of Infolytx, explains how his company's natural language processing technology is helping with clinical trial cohorts, and discusses how AI is gaining real traction elsewhere across healthcare.