Predicting brain age gap with radiomics and automl: A Promising approach for age-Related brain degeneration biomarkers.

Guo, Xiaoliang; Ding, Yanhui; Xu, Weizhi; Wang, Dong; Yu, Huiying; Lin, Yongkang; Chang, Shulei; Zhang, Qiqi; Zhang, Yongxin

Guo, Xiaoliang; Ding, Yanhui; Xu, Weizhi; Wang, Dong; Yu, Huiying; Lin, Yongkang; Chang, Shulei; Zhang, Qiqi; Zhang, Yongxin.

Afiliação

Guo X; School of Information Science and Engineering, Shandong Normal University, Jinan, China.
Ding Y; School of Information Science and Engineering, Shandong Normal University, Jinan, China. Electronic address: yanhuiding@126.com.
Xu W; School of Information Science and Engineering, Shandong Normal University, Jinan, China.
Wang D; School of Artificial Intelligence, Beijing University of Posts and Telecommunication, Beijing, China.
Yu H; School of Information Science and Engineering, Shandong Normal University, Jinan, China.
Lin Y; School of Information Science and Engineering, Shandong Normal University, Jinan, China.
Chang S; School of Information Science and Engineering, Shandong Normal University, Jinan, China.
Zhang Q; School of Information Science and Engineering, Shandong Normal University, Jinan, China.
Zhang Y; School of Mathematics and Statistics, Shandong Normal University, Jinan, China. Electronic address: yxzhang@sdnu.edu.cn.

J Neuroradiol ; 2023 Sep 16.

Article em En | MEDLINE | ID: mdl-37722591

Palavras-chave

Alzheimer'S disease; Automated machine learning; Brain age; Radiomics; Shapley additive explanations

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: J Neuroradiol Ano de publicação: 2023 Tipo de documento: Article País de afiliação: China

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