Development of Hybrid radiomic Machine learning models for preoperative prediction of meningioma grade on multiparametric MRI.

Journal: Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia

PMID: 40048835

PURPOSE: To develop and compare machine learning models for distinguishing low and high grade meningiomas on multiparametric MRI.

Steven Zhang

University of Adelaide, Adelaide, South Australia 5005, Australia.
Jesse Richter

College of Medicine and Public Health Flinders University Australia.
Jonathon Veale

College of Medicine and Public Health Flinders University Australia.
Vu Minh Hieu Phan

The Australian Institute for Machine Learning University of Adelaide Australia.
Nick Candy

Department of Neurosurgery Flinders Medical Centre Australia; Department of Surgery Otolaryngology Head and Neck Surgery University of Adelaide Australia.
Santosh Poonnoose

College of Medicine and Public Health Flinders University Australia; Department of Neurosurgery Flinders Medical Centre Australia.
Marc Agzarian

College of Medicine and Public Health Flinders University Australia; South Australia Medical Imaging Flinders Medical Centre Australia.
Minh-Son To

Health and Information, Adelaide, South Australia, Australia; Royal Adelaide Hospital, Adelaide, South Australia, Australia; Flinders Medical Centre, Flinders University, Adelaide, South Australia, Australia.

Adult Aged Female Humans Machine Learning Magnetic Resonance Imaging Male Meningeal Neoplasms Meningioma Middle Aged Multiparametric Magnetic Resonance Imaging Neoplasm Grading Radiomics Retrospective Studies

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