Combining Regional and Connectivity Metrics of Functional Magnetic Resonance Imaging and Diffusion Tensor Imaging for Individualized Prediction of Pain Sensitivity.

Zou, Rushi; Li, Linling; Zhang, Li; Huang, Gan; Liang, Zhen; Xiao, Lizu; Zhang, Zhiguo

Zou, Rushi; Li, Linling; Zhang, Li; Huang, Gan; Liang, Zhen; Xiao, Lizu; Zhang, Zhiguo.

Afiliação

Zou R; School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, China.
Li L; Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, Shenzhen University, Shenzhen, China.
Zhang L; Marshall Laboratory of Biomedical Engineering, Shenzhen, China.
Huang G; School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, China.
Liang Z; Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, Shenzhen University, Shenzhen, China.
Xiao L; Marshall Laboratory of Biomedical Engineering, Shenzhen, China.
Zhang Z; School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, China.

Front Mol Neurosci ; 15: 844146, 2022.

Article em En | MEDLINE | ID: mdl-35370547

Palavras-chave

DTI; fMRI; machine learning; pain sensitivity; regional-connectivity features

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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article

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