Clinical Value of Machine Learning in the Automated Detection of Focal Cortical Dysplasia Using Quantitative Multimodal Surface-Based Features

Clinical Value of Machine Learning in the Automated Detection of Focal Cortical Dysplasia Using Quantitative Multimodal Surface-Based Features

Objective: To automatically detect focal cortical dysplasia (FCD) lesion by combining quantitative multimodal surface-based features with machine learning and to assess its clinical value.Methods: Neuroimaging data and clinical information for 74 participants (40 with histologically proven FCD type...

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Bibliographic Details
Main Authors: Jia-Jie Mo, Jian-Guo Zhang, Wen-Ling Li, Chao Chen, Na-Jing Zhou, Wen-Han Hu, Chao Zhang, Yao Wang, Xiu Wang, Chang Liu, Bao-Tian Zhao, Jun-Jian Zhou, Kai Zhang
Format: Article
Language:English
Published: Frontiers Media S.A. 2019-01-01
Series:Frontiers in Neuroscience
Subjects:
focal cortical dysplasia
machine learning
metabolic
morphological
quantitative
Online Access:https://www.frontiersin.org/article/10.3389/fnins.2018.01008/full

Internet

https://www.frontiersin.org/article/10.3389/fnins.2018.01008/full

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