Open AccessMachine-Learning Approach to Differentiation of Benign and Malignant Peripheral Nerve Sheath Tumors: A Multicenter Study
Author(s) -
Michael Zhang,
Elizabeth Tong,
Forrest Hamrick,
Edward H. Lee,
Lydia Tam,
Courtney Pendleton,
Brandon W. Smith,
Nicholas F Hug,
Sandip Biswal,
Jayne Seekins,
Sarah A. Mattonen,
Sandy Napel,
Cynthia J. Campen,
Robert J. Spinner,
Kristen W. Yeom,
Thomas J. Wilson,
Mark A. Mahan
Publication year - 2021
Publication title -
neurosurgery/neurosurgery online
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.455
H-Index - 198
eISSN - 1081-1281
pISSN - 0148-396X
DOI - 10.1093/neuros/nyab212
Subject(s) - radiomics , magnetic resonance imaging , medicine , classifier (uml) , artificial intelligence , radiology , machine learning , computer science
Clinicoradiologic differentiation between benign and malignant peripheral nerve sheath tumors (PNSTs) has important management implications.