首页|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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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.”
TorontoCanadaNorth and Central Ameri caBrain Diseases and ConditionsCentral Nervous System Diseases and Condition sClinical ResearchClinical Trials and StudiesCyborgsEmerging Technologie sHealth and MedicineHydrocephalusIntracranial HypertensionMachine Learni ngSurgeryThird VentriculostomyVentriculostomy
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