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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Detalles Bibliográficos
Autores principales: Mo, Jia-Jie, Zhang, Jian-Guo, Li, Wen-Ling, Chen, Chao, Zhou, Na-Jing, Hu, Wen-Han, Zhang, Chao, Wang, Yao, Wang, Xiu, Liu, Chang, Zhao, Bao-Tian, Zhou, Jun-Jian, Zhang, Kai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2019
Materias:
Neuroscience
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6336916/
https://www.ncbi.nlm.nih.gov/pubmed/30686974
http://dx.doi.org/10.3389/fnins.2018.01008

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6336916/
https://www.ncbi.nlm.nih.gov/pubmed/30686974
http://dx.doi.org/10.3389/fnins.2018.01008

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