Development of a multi-feature-combined model: proof-of-concept with application to local failure prediction of post-SBRT or surgery early-stage NSCLC patients.

Yang, Zhenyu; Wang, Chunhao; Wang, Yuqi; Lafata, Kyle J; Zhang, Haozhao; Ackerson, Bradley G; Kelsey, Christopher; Tong, Betty; Yin, Fang-Fang

Yang, Zhenyu; Wang, Chunhao; Wang, Yuqi; Lafata, Kyle J; Zhang, Haozhao; Ackerson, Bradley G; Kelsey, Christopher; Tong, Betty; Yin, Fang-Fang.

Afiliación

Yang Z; Department of Radiation Oncology, Duke University, Durham, NC, United States.
Wang C; Medical Physics Graduate Program, Duke Kunshan University, Kunshan, Jiangsu, China.
Wang Y; Medical Physics Graduate Program, Duke University, Durham, NC, United States.
Lafata KJ; Department of Radiation Oncology, Duke University, Durham, NC, United States.
Zhang H; Medical Physics Graduate Program, Duke University, Durham, NC, United States.
Ackerson BG; Department of Radiation Oncology, Duke University, Durham, NC, United States.
Kelsey C; Department of Electrical and Computer Engineering, Duke University, Durham, NC, United States.
Tong B; Department of Radiology, Duke University, Durham, NC, United States.
Yin FF; Medical Physics Graduate Program, Duke Kunshan University, Kunshan, Jiangsu, China.

Front Oncol ; 13: 1185771, 2023.

Article en En | MEDLINE | ID: mdl-37781201

Palabras clave

SBRT; deep learning; early-stage lung NSCLC; local failure; machine learning (ML); surgery

Texto completo

Añadir a Mi BVS

Imprimir

XML

PubMed Links

Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Front Oncol Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Suiza

Texto completo

Añadir a Mi BVS

Imprimir

XML

PubMed Links

Buscar en Google