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Machine-Learning-Derived Nomogram Based on 3D Radiomic Features and Clinical Factors Predicts Progression-Free Survival in Lung Adenocarcinoma

BACKGROUND: To establish a machine-learning-derived nomogram based on radiomic features and clinical factors to predict post-surgical 2-year progression-free survival (PFS) in patients with lung adenocarcinoma. METHODS: Patients with >2 years post-surgical prognosis results of lung adenocarcinoma...

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Detalles Bibliográficos
Autores principales:	Liu, Guixue, Xu, Zhihan, Zhang, Yaping, Jiang, Beibei, Zhang, Lu, Wang, Lingyun, de Bock, Geertruida H., Vliegenthart, Rozemarijn, Xie, Xueqian
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Frontiers Media S.A. 2021
Materias:	Oncology
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8260977/ https://www.ncbi.nlm.nih.gov/pubmed/34249741 http://dx.doi.org/10.3389/fonc.2021.692329

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