A study of aortic dissection screening method based on multiple machine learning models.

Liu, Lijue; Zhang, Caiwang; Zhang, Guogang; Gao, Yan; Luo, Jingmin; Zhang, Wei; Li, Yi; Mu, Yang

Liu, Lijue; Zhang, Caiwang; Zhang, Guogang; Gao, Yan; Luo, Jingmin; Zhang, Wei; Li, Yi; Mu, Yang.

Afiliação

Liu L; School of Information Science and Engineering, Central South University, Changsha 410075, China.
Zhang C; Hunan Zixing Artificial Intelligence Research Institute, Changsha 410007, China.
Zhang G; School of Information Science and Engineering, Central South University, Changsha 410075, China.
Gao Y; Xiangya Hospital, Central South University, Changsha 410008, China.
Luo J; School of Information Science and Engineering, Central South University, Changsha 410075, China.
Zhang W; Xiangya Hospital, Central South University, Changsha 410008, China.
Li Y; Xiangya Hospital, Central South University, Changsha 410008, China.
Mu Y; School of Information Science and Engineering, Central South University, Changsha 410075, China.

J Thorac Dis ; 12(3): 605-614, 2020 Mar.

Article em En | MEDLINE | ID: mdl-32274126

Palavras-chave

Aortic dissection (AD); class imbalance; machine learning; screening performance

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Screening_studies Idioma: En Ano de publicação: 2020 Tipo de documento: Article

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