University of Toronto Reports Findings in Hydrocephalus (Does machine learning i mprove prediction accuracy of the Endoscopic Third Ventriculostomy Success Score ? A contemporary Hydrocephalus Clinical Research Network cohort study)
University of Toronto Reports Findings in Hydrocephalus (Does machine learning i mprove prediction accuracy of the Endoscopic Third Ventriculostomy Success Score ? A contemporary Hydrocephalus Clinical Research Network cohort study)
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Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – New research on Central Nervous System Diseases and Conditions - Hydrocephalusis the subject of a report. According t o news reporting originating in Toronto, Canada, by NewsRxjournalists, research stated, “This Hydrocephalus Clinical Research Network (HCRN) study had two aims: (1) to compare the predictive performance of the original ETV Success Score (E TVSS) using logisticregression modeling with other newer machine learning model s and (2) to assess whether inclusion ofimaging variables improves prediction p erformance using machine learning models. We identified childrenundergoing firs t-time ETV for hydrocephalus that were enrolled prospectively at HCRN sites betw een 200and 2020.”
Key words
Toronto/Canada/North and Central Ameri ca/Brain Diseases and Conditions/Central Nervous System Diseases and Condition s/Clinical Research/Clinical Trials and Studies/Cyborgs/Emerging Technologie s/Health and Medicine/Hydrocephalus/Intracranial Hypertension/Machine Learni ng/Surgery/Third Ventriculostomy/Ventriculostomy
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