Journal
PEDIATRIC NEPHROLOGY
Volume 33, Issue 10, Pages 1625-1627Publisher
SPRINGER
DOI: 10.1007/s00467-018-4021-4
Keywords
Artificial intelligence; Machine learning; Renal dialysis; Body water; Child
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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.
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