Machine learning-based radiomics nomograms to predict number of fields in postoperative IMRT for breast cancer.

Mao, Yichen; Di, Wenyi; Zong, Dan; Mu, Zhongde; He, Xia

Mao, Yichen; Di, Wenyi; Zong, Dan; Mu, Zhongde; He, Xia.

Afiliación

Mao Y; The Affiliated Cancer Hospital of Nanjing Medical University & Jiangsu Institute of Cancer Research & Jiangsu Cancer Hospital, Nanjing, China.
Di W; The Affiliated Cancer Hospital of Nanjing Medical University & Jiangsu Institute of Cancer Research & Jiangsu Cancer Hospital, Nanjing, China.
Zong D; The Affiliated Cancer Hospital of Nanjing Medical University & Jiangsu Institute of Cancer Research & Jiangsu Cancer Hospital, Nanjing, China.
Mu Z; The Affiliated Cancer Hospital of Nanjing Medical University & Jiangsu Institute of Cancer Research & Jiangsu Cancer Hospital, Nanjing, China.
He X; The Affiliated Cancer Hospital of Nanjing Medical University & Jiangsu Institute of Cancer Research & Jiangsu Cancer Hospital, Nanjing, China.

J Appl Clin Med Phys ; 25(3): e14194, 2024 Mar.

Article en En | MEDLINE | ID: mdl-37910655

Asunto(s)

Neoplasias de la Mama; Radioterapia de Intensidad Modulada; Humanos; Femenino; Neoplasias de la Mama/radioterapia; Neoplasias de la Mama/cirugía; Nomogramas; Radiómica; Estudios Retrospectivos; Aprendizaje Automático

Palabras clave

breast cancer; machine learning; number of fields; radiomics; radiotherapy

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Neoplasias de la Mama / Radioterapia de Intensidad Modulada Límite: Female / Humans Idioma: En Revista: J Appl Clin Med Phys Asunto de la revista: BIOFISICA Año: 2024 Tipo del documento: Article País de afiliación: China

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