Machine Learning for Endometrial Cancer Prediction and Prognostication.

Bhardwaj, Vipul; Sharma, Arundhiti; Parambath, Snijesh Valiya; Gul, Ijaz; Zhang, Xi; Lobie, Peter E; Qin, Peiwu; Pandey, Vijay

Bhardwaj, Vipul; Sharma, Arundhiti; Parambath, Snijesh Valiya; Gul, Ijaz; Zhang, Xi; Lobie, Peter E; Qin, Peiwu; Pandey, Vijay.

Afiliación

Bhardwaj V; Tsinghua Berkeley Shenzhen Institute, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, China.
Sharma A; Tsinghua Berkeley Shenzhen Institute, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, China.
Parambath SV; Division of Molecular Medicine, St. John's Research Institute, Bangalore, India.
Gul I; Institute of Biopharmaceutical and Health Engineering, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, China.
Zhang X; Shenzhen Bay Laboratory, Shenzhen, China.
Lobie PE; Tsinghua Berkeley Shenzhen Institute, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, China.
Qin P; Institute of Biopharmaceutical and Health Engineering, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, China.
Pandey V; Shenzhen Bay Laboratory, Shenzhen, China.

Front Oncol ; 12: 852746, 2022.

Article en En | MEDLINE | ID: mdl-35965548

Palabras clave

algorithm; artificial intelligence; deep learning; endometrial cancer; histopathology; machine learning; prediction model

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Front Oncol Año: 2022 Tipo del documento: Article País de afiliación: China Pais de publicación: Suiza

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