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

Purpose: To develop and validate a clinico-biological features and 18F-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 carcin...

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Bibliographic Details

Published in:	European Journal of Nuclear Medicine & Molecular Imaging Vol. 48; no. 5; pp. 1538 - 1550
Main Authors:	Ren, Caiyue, Zhang, Jianping, Qi, Ming, Zhang, Jiangang, Zhang, Yingjian, Song, Shaoli, Sun, Yun, Cheng, Jingyi
Format:	Journal Article
Published:	Springer Nature May2021
Online Access:	View this record in EBSCOhost