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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Detalhes bibliográficos
Publicado no:Eur J Nucl Med Mol Imaging
Main Authors: Ren, Caiyue, Zhang, Jianping, Qi, Ming, Zhang, Jiangang, Zhang, Yingjian, Song, Shaoli, Sun, Yun, Cheng, Jingyi
Formato: Artigo
Idioma:Inglês
Publicado em: Springer Berlin Heidelberg 2020
Assuntos:
Original Article
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC8113203/
https://ncbi.nlm.nih.gov/pubmed/33057772
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/s00259-020-05065-6
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