Related Experiment Video
Updated: Feb 7, 2026

Making MR Imaging Child's Play - Pediatric Neuroimaging Protocol, Guidelines and Procedure
Published on: July 30, 2009
Beyond playing games: nephrologist vs machine in pediatric dialysis prescribing
Wesley Hayes1,2, Marco Allinovi3
1Great Ormond Street Hospital, London, UK. Wesley.hayes@gosh.nhs.uk.
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.
Related Concept Videos
Social Foundations of Self I: Play and Game
Dialysis
Acute kidney injury develops suddenly and can be caused by pre-renal causes (e.g., hypovolemia, shock), intrinsic renal causes (e.g., acute tubular necrosis), or post-renal causes (e.g., urinary obstruction). In contrast, chronic renal failure progresses gradually over time and is often...
Dialysis
Peritoneal Dialysis II: Peritoneal Dialysis Systems and Complications
Machines
A free-body diagram of the...
Peritoneal Dialysis I: Introduction and Procedure

