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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."

 

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.
 

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.
 

Building a collaborative approach to patient-centric artificial intelligence initiatives

(Sponsored) GE Healthcare offers a preview of how its new Edison platform will improve workflow, clinical insight and patient satisfaction.

 

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.