Development of a Machine-Learning Algorithm to Identify Cauda Equina Compression on Magnetic Resonance Imaging Scans

Cauda equina syndrome (CES) poses significant neurological risks if untreated. Diagnosis relies on clinical and radiological features. As the symptoms are often nonspecific and common, the diagnosis is usually made after a magnetic resonance imaging (MRI) scan. A huge number of MRI scans are done to...

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Bibliographic Details
Published in:	World neurosurgery Vol. 195; p. 123669
Main Authors:	Biswas, Sayan, Sarkar, Ved, MacArthur, Joshua Ian, Guo, Li, Deng, Xutao, Snowdon, Ella, Ahmed, Hamza, Tetlow, Callum, George, K. Joshi
Format:	Journal Article
Language:	English
Published:	United States Elsevier Inc 01.03.2025
Subjects:	Adult Algorithms Cauda equina compression Cauda Equina Syndrome - diagnostic imaging CNN Female Humans Machine Learning Magnetic Resonance Imaging - methods Male Mid-sagittal MRI Middle Aged Neural Networks, Computer Neurosurgery Sensitivity and Specificity CEC CNN MRI Cauda equina compression Grad-CAM DP CES GIRFT VGG NHS Mid-sagittal MRI PCR ML Prolapse to canal ratio Disc prolapse Visual Geometry Group National Health Service Magnetic resonance imaging Cauda equina syndrome Machine-learning Get It Right First Time Gradient-weighted Class Activation Mapping
ISSN:	1878-8750, 1878-8769, 1878-8769
Online Access:	Get full text
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