Predicting anaplastic lymphoma kinase rearrangement status in patients with non-small cell lung cancer using a machine learning algorithm that combines clinical features and CT images.

Hao, Peng; Deng, Bo-Yu; Huang, Chan-Tao; Xu, Jun; Zhou, Fang; Liu, Zhe-Xing; Zhou, Wu; Xu, Yi-Kai

Hao, Peng; Deng, Bo-Yu; Huang, Chan-Tao; Xu, Jun; Zhou, Fang; Liu, Zhe-Xing; Zhou, Wu; Xu, Yi-Kai.

Afiliación

Hao P; Nanfang Hospital, Southern Medical University, Guangzhou, China.
Deng BY; School of Medical Information Engineering, Guangzhou University of Chinese Medicine, Guangzhou, China.
Huang CT; Nanfang Hospital, Southern Medical University, Guangzhou, China.
Xu J; Nanfang Hospital, Southern Medical University, Guangzhou, China.
Zhou F; Nanfang Hospital, Southern Medical University, Guangzhou, China.
Liu ZX; School of Biomedical Engineering, Southern Medical Uinversity, Guangzhou, China.
Zhou W; School of Medical Information Engineering, Guangzhou University of Chinese Medicine, Guangzhou, China.
Xu YK; Nanfang Hospital, Southern Medical University, Guangzhou, China.

Front Oncol ; 12: 994285, 2022.

Article en En | MEDLINE | ID: mdl-36338735

Palabras clave

X-ray computed; anaplastic lymphoma kinase; gene mutation; machine learning; non-small cell lung cancer; texture; tomography

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Texto completo: 1 Colección: 01-internacional Banco 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

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