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Machine learning models predict overall survival and progression free survival of non-surgical esophageal cancer patients with chemoradiotherapy based on CT image radiomics signatures

PURPOSE: To construct machine learning models for predicting progression free survival (PFS) and overall survival (OS) with esophageal squamous cell carcinoma (ESCC) patients. METHODS: 204 ESCC patients were randomly divided into training cohort (n = 143) and test cohort (n = 61) according to the ra...

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Detalles Bibliográficos
Autores principales:	Cui, Yongbin, Li, Zhengjiang, Xiang, Mingyue, Han, Dali, Yin, Yong, Ma, Changsheng
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	BioMed Central 2022
Materias:	Research
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9795769/ https://www.ncbi.nlm.nih.gov/pubmed/36575480 http://dx.doi.org/10.1186/s13014-022-02186-0

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