Artificial intelligence based treatment planning of radiotherapy for locally advanced breast cancer.

van de Sande, Dennis; Sharabiani, Marjan; Bluemink, Hanneke; Kneepkens, Esther; Bakx, Nienke; Hagelaar, Els; van der Sangen, Maurice; Theuws, Jacqueline; Hurkmans, Coen

van de Sande, Dennis; Sharabiani, Marjan; Bluemink, Hanneke; Kneepkens, Esther; Bakx, Nienke; Hagelaar, Els; van der Sangen, Maurice; Theuws, Jacqueline; Hurkmans, Coen.

Afiliación

van de Sande D; Catharina Hospital, Department of Radiation Oncology, Eindhoven, the Netherlands.
Sharabiani M; European Organisation for Research and Treatment of Cancer (EORTC) Headquarters, Brussels, Belgium.
Bluemink H; Catharina Hospital, Department of Radiation Oncology, Eindhoven, the Netherlands.
Kneepkens E; Catharina Hospital, Department of Radiation Oncology, Eindhoven, the Netherlands.
Bakx N; Catharina Hospital, Department of Radiation Oncology, Eindhoven, the Netherlands.
Hagelaar E; Catharina Hospital, Department of Radiation Oncology, Eindhoven, the Netherlands.
van der Sangen M; Catharina Hospital, Department of Radiation Oncology, Eindhoven, the Netherlands.
Theuws J; Catharina Hospital, Department of Radiation Oncology, Eindhoven, the Netherlands.
Hurkmans C; Catharina Hospital, Department of Radiation Oncology, Eindhoven, the Netherlands.

Phys Imaging Radiat Oncol ; 20: 111-116, 2021 Oct.

Article en En | MEDLINE | ID: mdl-34917779

Palabras clave

Convolutional neural networks; Dose mimicking; Dose prediction; Locally advanced breast cancer; Machine learning

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Guideline / Prognostic_studies Idioma: En Revista: Phys Imaging Radiat Oncol Año: 2021 Tipo del documento: Article País de afiliación: Países Bajos Pais de publicación: Países Bajos

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