Deep learning radiomic nomogram can predict the number of lymph node metastasis in locally advanced gastric cancer: an international multicenter study

doi:10.1016/j.annonc.2020.04.003

CORC > 自动化研究所 > 中国科学院自动化研究所 > 中国科学院分子影像重点实验室

	Deep learning radiomic nomogram can predict the number of lymph node metastasis in locally advanced gastric cancer: an international multicenter study
	Dong, D.6,7; Fang, M. -J.6,7; Tang, L.8; Shan, X. -H.9; Gao, J. -B.10; Giganti, F.11,12,13; Wang, R. -P.1; Chen, X.4,5; Wang, X. -X.9; Palumbo, D.3,13
刊名	ANNALS OF ONCOLOGY
	2020-07-01
卷号	31 期号:7 页码:912-920
ISSN号	0923-7534
DOI	10.1016/j.annonc.2020.04.003
通讯作者	Ji, J. -F.(jijiafu@hsc.pku.edu.cn) ; Liu, Z. -Y.(zyliu@163.com) ; Tian, J.(jie.tian@ia.ac.cn)
资助项目	National Natural Science Foundation of China[91959130] ; National Natural Science Foundation of China[81971776] ; National Natural Science Foundation of China[81771924] ; National Natural Science Foundation of China[81930053] ; National Natural Science Foundation of China[81771912] ; National Natural Science Foundation of China[81671682] ; National Natural Science Foundation of China[91959205] ; National Natural Science Foundation of China[81601469] ; National Natural Science Foundation of China[81701687] ; National Natural Science Foundation of China[81227901] ; National Science Fund for Distinguished Young Scholars[81925023] ; National Key R&D Program of China[2017YFA0205200] ; National Key R&D Program of China[2017YFC1308700] ; National Key R&D Program of China[2017YFC1309100] ; National Key R&D Program of China[2017YFC1309101] ; National Key R&D Program of China[2017YFC1309104] ; Beijing Natural Science Foundation[L182061] ; Beijing Natural Science Foundation[Z180001] ; Youth Innovation Promotion Association CAS[2017175] ; UCL Graduate Research Scholarship ; Brahm PhD scholarship in memory of Chris Adams
WOS关键词	DIAGNOSIS ; SURVIVAL
WOS研究方向	Oncology
语种	英语
出版者	ELSEVIER
WOS记录号	WOS:000540695500014
资助机构	National Natural Science Foundation of China ; National Science Fund for Distinguished Young Scholars ; National Key R&D Program of China ; Beijing Natural Science Foundation ; Youth Innovation Promotion Association CAS ; UCL Graduate Research Scholarship ; Brahm PhD scholarship in memory of Chris Adams
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/39765]
专题	自动化研究所_中国科学院分子影像重点实验室
通讯作者	Ji, J. -F.; Liu, Z. -Y.; Tian, J.
作者单位	1.Guizhou Prov Peoples Hosp, Dept Radiol, Guiyang, Guizhou, Peoples R China 2.Peking Univ Canc Hosp & Inst, Key Lab Carcinogenesis & Translat Res, Gastrointestinal Canc Ctr, Minist Educ Beijing, 52 Fu Cheng Rd, Beijing 100142, Peoples R China 3.Univ Vita Salute San Raffaele, Milan, Italy 4.Guangzhou First Peoples Hosp, Dept Radiol, Guangzhou, Guangdong, Peoples R China 5.Guangdong Prov Peoples Hosp, Guangdong Acad Med Sci, Dept Radiol, Guangzhou, Guangdong, Peoples R China 6.Chinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, 95 Zhongguancun East Rd, Beijing 100190, Peoples R China 7.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing, Peoples R China 8.Peking Univ Canc Hosp & Inst, Key Lab Carcinogenesis & Translat Res, Radiol Dept, Minist Educ Beijing, Beijing, Peoples R China 9.Jiangsu Univ, Dept Radiol, Affiliated Peoples Hosp, Zhenjiang, Jiangsu, Peoples R China 10.Zhengzhou Univ, Dept Radiol, Affiliated Hosp 1, Zhengzhou, Henan, Peoples R China
推荐引用方式 GB/T 7714	Dong, D.,Fang, M. -J.,Tang, L.,et al. Deep learning radiomic nomogram can predict the number of lymph node metastasis in locally advanced gastric cancer: an international multicenter study[J]. ANNALS OF ONCOLOGY,2020,31(7):912-920.
APA	Dong, D..,Fang, M. -J..,Tang, L..,Shan, X. -H..,Gao, J. -B..,...&Tian, J..(2020).Deep learning radiomic nomogram can predict the number of lymph node metastasis in locally advanced gastric cancer: an international multicenter study.ANNALS OF ONCOLOGY,31(7),912-920.
MLA	Dong, D.,et al."Deep learning radiomic nomogram can predict the number of lymph node metastasis in locally advanced gastric cancer: an international multicenter study".ANNALS OF ONCOLOGY 31.7(2020):912-920.