CT-based radiomics signatures can predict the tumor response of non-small cell lung cancer patients treated with first-line chemotherapy and targeted therapy-Reference-Cited by-同舟云学术

CT-based radiomics signatures can predict the tumor response of non-small cell lung cancer patients treated with first-line chemotherapy and targeted therapy

Published:2021-09-26 Issue: Volume: Page:
ISSN:0938-7994
Container-title:European Radiology
language:en
Short-container-title:Eur Radiol

Author:

Yang Fengchang,Zhang Jiayi,Zhou Liu,Xia Wei,Zhang Rui,Wei Haifeng,Feng Jinxue,Zhao Xingyu,Jian Junming,Gao Xin,Yuan Shuanghu^ORCID

Funder

National Natural Science Foundation of China

Shandong Key Research and Development Plan

Guangdong Provincial Key Research and Development Program

Chinese Academy of Sciences-Iranian Vice Presidency for Science and Technology Silk Road Science Fund

Science and Technology Plan Projects of Jiangsu

Outstanding Youth Natural Science Foundation of Shandong Province

Jinan Clinical Medicine Science and Technology Innovation Plan

National Key Research and Development Program of China

Publisher

Springer Science and Business Media LLC

Subject

Radiology Nuclear Medicine and imaging,General Medicine

Link

https://link.springer.com/content/pdf/10.1007/s00330-021-08277-y.pdf

Reference49 articles.

1. Siegel RL, Miller KD, Jemal A (2019) Cancer statistics. CA Cancer J Clin 69(1):7–34

2. Jemal A, Siegel R, Ward E et al (2008) Cancer statistics. CA Cancer J Clin 58(2):71–96

3. Cancer Research UK. Types of lung cancer. www.cancerresearchuk.org/about-cancer/lung-cancer/stages-typesgrades/types. Accessed 25 Sep 2019

4. American cancer society. Survival rates for non-small cell lung cancer. www.cancer.org. Accessed 21 Mar 2020

5. Eberhardt WE, De Ruysscher D, Weder W et al (2015) 2nd ESMO Consensus Conference in Lung Cancer: locally advanced stage III non-small-cell lung cancer. Ann Oncol 26(8):1573–1588

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