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Machine learning based on clinico-biological features integrated (18)F-FDG PET/CT radiomics for distinguishing squamous cell carcinoma from adenocarcinoma of lung

PURPOSE: To develop and validate a clinico-biological features and (18)F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) radiomic-based nomogram via machine learning for the pretherapy prediction of discriminating between adenocarcinoma (ADC) and squamous cell carc...

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Detalles Bibliográficos
Autores principales:	Ren, Caiyue, Zhang, Jianping, Qi, Ming, Zhang, Jiangang, Zhang, Yingjian, Song, Shaoli, Sun, Yun, Cheng, Jingyi
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Springer Berlin Heidelberg 2020
Materias:	Original Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8113203/ https://www.ncbi.nlm.nih.gov/pubmed/33057772 http://dx.doi.org/10.1007/s00259-020-05065-6

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