Machine Learning & AI for Healthcare

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 to improve patient outcomes and financial return.

Automating machine learning and artificial intelligence improves the speed and accuracy of predictive models, says DataRobot GM of Healthcare Colleen Greene.

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

GE Healthcare's Karley Yoder offers a preview of how the organization's new Edison platform will improve workflow, clinical insight and patient satisfaction.

Leonard D'Avolio, founder and CEO of Cyft, says machine learning can help organizations learn from data more quickly and intuitively.

Partners HealthCare Pivot Labs is enabling collaboration between hospitals, health systems and other stakeholders such as big tech and pharma, says digital health scientist Dr. Sujay Kakarmath.

Westchester Medical Center integrated data from the EHR using a machine learning algorithm to connect patients to the right sources of care, says Director of Data Management & Analytics Simer Sodhi.

Infolytx's natural language processing technology is helping with clinical trial cohorts, explains CEO Badrul Husain.

Tej Anand, professor of practice at the University of Texas' McCombs School of Business, explains how blockchain can help eliminate "redundant work, rework and reconciliation."

Chad Konchak, assistant vice president of Clinical Analytics at NorthShore University HealthSystem, says the challenge is in the cultural maturity for people to realize what the data can do for them.