Development and Validation of a Deep Learning Model for Non–Small Cell Lung Cancer Survival-Reference-Cited by-同舟云学术

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Development and Validation of a Deep Learning Model for Non–Small Cell Lung Cancer Survival

Published:2020-06-03 Issue:6 Volume:3 Page:e205842
ISSN:2574-3805
Container-title:JAMA Network Open
language:en
Short-container-title:JAMA Netw Open

Author:

She Yunlang¹,Jin Zhuochen²,Wu Junqi¹,Deng Jiajun¹,Zhang Lei¹,Su Hang¹,Jiang Gening¹,Liu Haipeng³,Xie Dong¹,Cao Nan²⁴,Ren Yijiu¹,Chen Chang¹

Affiliation:

1. Department of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China

2. College of Design and Innovation, Tongji University, Shanghai, China

3. Shanghai Key Laboratory of Tuberculosis, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China

4. Computer Science, NYU Shanghai, Shanghai, China

Publisher

American Medical Association (AMA)

Subject

General Medicine

Link

https://jamanetwork.com/journals/jamanetworkopen/articlepdf/2766666/she_2020_oi_200272.pdf

Reference48 articles.

1. Cancer statistics in China, 2015.;Chen;CA Cancer J Clin,2016

2. The International Association for the Study of Lung Cancer Staging Project: prognostic factors and pathologic TNM stage in surgically managed non-small cell lung cancer.;Chansky;J Thorac Oncol,2009

3. Performance status and smoking status are independent favorable prognostic factors for survival in non-small cell lung cancer: a comprehensive analysis of 26,957 patients with NSCLC.;Kawaguchi;J Thorac Oncol,2010

4. Development and validation of a nomogram for predicting survival in patients with resected non-small-cell lung cancer.;Liang;J Clin Oncol,2015

5. Nomograms predict overall survival for patients with small-cell lung cancer incorporating pretreatment peripheral blood markers.;Xie;J Thorac Oncol,2015

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