Comparison of machine learning methods for the detection of focal cortical dysplasia lesions: decision tree, support vector machine and artificial neural network-Reference-Cited by-同舟云学术

Comparison of machine learning methods for the detection of focal cortical dysplasia lesions: decision tree, support vector machine and artificial neural network

Published:2022-08-18 Issue:12 Volume:44 Page:1142-1149
ISSN:0161-6412
Container-title:Neurological Research
language:en
Short-container-title:Neurological Research

Author:

Ganji Zohreh¹,Aghaee Hakak Mohsen²,Zare Hoda¹³

Affiliation:

1. Department of Medical Physics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran

2. Epilepsy Monitoring Unit, Research and Education Department, Razavi Hospital, Mashhad, Iran

3. Medical Physics Research Center, Mashhad University of Medical Sciences, Mashhad, Iran

Funder

supported

Publisher

Informa UK Limited

Subject

Neurology (clinical),Neurology,General Medicine

Link

https://www.tandfonline.com/doi/pdf/10.1080/01616412.2022.2112381

Reference29 articles.

1. Automated detection of focal cortical dysplasia lesions using computational models of their MRI characteristics and texture analysis

2. Surgery for malformations of cortical development causing epilepsy

3. Cortical feature analysis and machine learning improves detection of “MRI-negative” focal cortical dysplasia

4. A Survey on Computer-Aided Diagnosis of Brain Disorders through MRI Based on Machine Learning and Data Mining Methodologies with an Emphasis on Alzheimer Disease Diagnosis and the Contribution of the Multimodal Fusion

5. Detection of Lesions Underlying Intractable Epilepsy on T1-Weighted MRI as an Outlier Detection Problem

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