Children's National Health to apply AI to study ICU transitions

Washington, D.C.-based Children's National Health System formed a research collaboration with KenSci, an artificial intelligence-powered risk prediction platform, to study how pediatric risk scores can be improved for clinical decision making.

Through the partnership, Children's National will leverage KenSci's AI platform to test predictive patient models it previously developed to study transitions to and from intensive care units. Models from George Washington University will also be tested.

"Since the mid-80s we have been able to predict mortality risks in pediatric ICUs using risk scores. In most cases these scores are used for quality assessment," said Murray Pollack, MD, outcomes research director at Children's National, according to a news release emailed to Becker's Hospital Review. "Our collaborative goals are to study the temporal variation in data, taking the first step towards dynamic risk scoring for pediatric ICUs."  

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