机构:[1]Department of Epidemiology and Biostatistics, School of Population Medicine and Public Health, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China[2]Department of Cancer Epidemiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and PekingUnion Medical College, Beijing 100021, China[3]School of Public Health,Dalian Medical University, Dalian, China[4]Diagnosis and Treatment for Cervical Lesions Center, Shenzhen Maternity & Child Healthcare Hospital,Shenzhen, China深圳市妇幼保健院深圳市康宁医院深圳医学信息中心[5]Tencent Jarvis Lab, Shenzhen, China[6]Zonsun Healthcare,Shenzhen, China[7]Center for Cancer Prevention Research, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China四川省人民医院四川省肿瘤医院[8]Tencent Healthcare, Shenzhen, China[9]Jiangxi Maternal and Child Health Hospital,Nanchang, China[10]Chengdu Women’s and Children’s Central Hospital,School of Medicine, University of Electronic Science and Technology ofChina, Chengdu, China四川省人民医院[11]Chongqing University Cancer Hospital, Chongqing,China[12]Cancer Hospital of China Medical University, Liaoning Cancer Hospital & Institute, Shenyang, China[13]Affiliated Cancer Hospital of Zhengzhou University/Henan Cancer Hospital, Zhengzhou, China河南省肿瘤医院[14]Department of Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China[15]Department of Gynecology, Shenzhen Maternity & Child Healthcare Hospital, Shenzhen,China深圳市妇幼保健院深圳市康宁医院深圳医学信息中心
This work was supported by the Chinese Academy of Medical Science Initiative for Innovative Medicine (grant CIFMS2017-I2M-B&R-03); the National Key Technology R&D Program (grant 2018YFC1315504); Ministry of Science and Technology of China, the Key Area Research and Development Program of Guangdong Province, China (grant 2018B010111001); Science and Technology Program of Shenzhen, China (grant ZDSYS201802021814180); and Sanming Project of Medicine in Shenzhen (grant SZSM201612042).
第一作者机构:[1]Department of Epidemiology and Biostatistics, School of Population Medicine and Public Health, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China[2]Department of Cancer Epidemiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and PekingUnion Medical College, Beijing 100021, China
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通讯作者:
推荐引用方式(GB/T 7714):
Peng Xue,Chao Tang,Qing Li,et al.Development and validation of an artificial intelligence system for grading colposcopic impressions and guiding biopsies(Open Access)[J].BMC MEDICINE.2020,18(1):doi:10.1186/s12916-020-01860-y.
APA:
Peng Xue,Chao Tang,Qing Li,Yuexiang Li,Yu Shen...&Fanghui Zhao.(2020).Development and validation of an artificial intelligence system for grading colposcopic impressions and guiding biopsies(Open Access).BMC MEDICINE,18,(1)
MLA:
Peng Xue,et al."Development and validation of an artificial intelligence system for grading colposcopic impressions and guiding biopsies(Open Access)".BMC MEDICINE 18..1(2020)