MRI Radiomics-Based Machine Learning Models for Ki67 Expression and Gleason Grade Group Prediction in Prostate Cancer.

Qiao, Xiaofeng; Gu, Xiling; Liu, Yunfan; Shu, Xin; Ai, Guangyong; Qian, Shuang; Liu, Li; He, Xiaojing; Zhang, Jingjing

Qiao, Xiaofeng; Gu, Xiling; Liu, Yunfan; Shu, Xin; Ai, Guangyong; Qian, Shuang; Liu, Li; He, Xiaojing; Zhang, Jingjing.

Afiliação

Qiao X; Department of Radiology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing 400010, China.
Gu X; Department of Radiology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing 400010, China.
Liu Y; Department of Radiology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing 400010, China.
Shu X; Department of Radiology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing 400010, China.
Ai G; Department of Radiology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing 400010, China.
Qian S; Big Data and Software Engineering College, Chongqing University, Chongqing 400000, China.
Liu L; Big Data and Software Engineering College, Chongqing University, Chongqing 400000, China.
He X; Department of Radiology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing 400010, China.
Zhang J; Departments of Diagnostic Radiology, National University of Singapore, Singapore 119074, Singapore.

Cancers (Basel) ; 15(18)2023 Sep 13.

Article em En | MEDLINE | ID: mdl-37760505

Palavras-chave

Gleason grade group; Ki67; MRI; machine learning; prostate cancer

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

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