Revisiting the Endoscopic Third Ventriculostomy Success Score using machine learning: can we do better?

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Bibliographic Details
Title:	Revisiting the Endoscopic Third Ventriculostomy Success Score using machine learning: can we do better?
Authors:	Adil SM; Departments of1Neurosurgery and., Seas A; Departments of1Neurosurgery and.; 2Department of Biomedical Engineering, Duke University, Durham, North Carolina; and., Sexton DP; Departments of1Neurosurgery and., Warman PI; Departments of1Neurosurgery and., Wissel BD; Departments of1Neurosurgery and., Carpenter KL; Departments of1Neurosurgery and., Carter L; 3Department of Pediatrics, Division of Pediatric Neurosurgery, Prisma Health Greenville Memorial Hospital, Greenville, South Carolina., Kolls BJ; 4Neurology, Duke University Medical Center, Durham, North Carolina., Fuller AT; Departments of1Neurosurgery and., Lad SP; Departments of1Neurosurgery and., Dunn TW; Departments of1Neurosurgery and.; 2Department of Biomedical Engineering, Duke University, Durham, North Carolina; and., Fuchs H; Departments of1Neurosurgery and., Vestal M; Departments of1Neurosurgery and., Grant GA; Departments of1Neurosurgery and.
Source:	Journal of neurosurgery. Pediatrics [J Neurosurg Pediatr] 2024 Dec 06; Vol. 35 (3), pp. 246-254. Date of Electronic Publication: 2024 Dec 06 (Print Publication: 2025).
Publication Type:	Journal Article
Journal Info:	Publisher: American Association of Neurological Surgeons Country of Publication: United States NLM ID: 101463759 Publication Model: Electronic-Print Cited Medium: Internet ISSN: 1933-0715 (Electronic) Linking ISSN: 19330707 NLM ISO Abbreviation: J Neurosurg Pediatr Subsets: MEDLINE
Database:	MEDLINE Ultimate

Description
ISSN:	1933-0715
DOI:	10.3171/2024.9.PEDS24146