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Beyond playing games: nephrologist vs machine in pediatric dialysis prescribing.

ABSTRACT: In a recent article in Pediatric Nephrology, Olivier Niel and colleagues applied an artificial intelligence algorithm to a clinical problem that continues to challenge experienced pediatric nephrologists: optimizing the target weight of children on dialysis. They compared blood pressure, antihypertensive medication and intradialytic symptoms in children whose target weight was prescribed firstly by a nephrologist, then subsequently using a machine learning algorithm. Improvements in all outcome measures are reported. Their innovative approach to tackling this important clinical problem appears promising. In this editorial, we discuss the strengths and weaknesses of their study and consider to what extent machine learning strategies are suited to optimizing pediatric dialysis outcomes.

SUBMITTER: Hayes W

PROVIDER: S-EPMC6132900 | biostudies-other | 2018 Jul

REPOSITORIES: biostudies-other

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Beyond playing games: nephrologist vs machine in pediatric dialysis prescribing.

Hayes Wesley W Allinovi Marco M

Pediatric nephrology (Berlin, Germany) 20180712 10

In a recent article in Pediatric Nephrology, Olivier Niel and colleagues applied an artificial intelligence algorithm to a clinical problem that continues to challenge experienced pediatric nephrologists: optimizing the target weight of children on dialysis. They compared blood pressure, antihypertensive medication and intradialytic symptoms in children whose target weight was prescribed firstly by a nephrologist, then subsequently using a machine learning algorithm. Improvements in all outcome ...[more]

PMID: 30003314

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