Page 57 - 中国全科医学2022-18
P. 57
·2230· http://www.chinagp.net E-mail:zgqkyx@chinagp.net.cn
papillomavirus prevalence in 5 continents:meta-analysis of 1 million cnki.cjcor.2020.02.02.
women with normal cytological findings[J]. J Infect Dis,2010, [15]李双,李明珠,丛青,等 . 人乳头瘤病毒疫苗临床应用中国专
202(12):1789-1799. DOI:10.1086/657321. 家共识[J]. 中国妇产科临床杂志,2021,22(2):225-234.
[11]ZHU B,LIU Y,ZUO T,et al. The prevalence,trends,and DOI:10.13390/j.issn.1672-1861.2021.02.045.
geographical distribution of human papillomavirus infection in LI S,LI M Z,CONG Q,et al. Chinese expert consensus on
China:the pooled analysis of 1.7 million women[J]. Cancer clinical application of human papillomavirus vaccine[J]. Chin J
Med,2019,8(11):5373-5385. DOI:10.1002/cam4.2017. Clin Obstet Gynecol,2021,22(2):225-234. DOI:10.13390/
[12]中国医师协会全科医师分会,北京妇产学会社区与基层分会 . j.issn.1672-1861.2021.02.045.
[16]高维娇,高雨农 . 宫颈癌筛查中人乳头状瘤病毒检测现状[J].
更年期妇女健康管理专家共识(基层版)[J].中国全科医
肿瘤综合治疗电子杂志,2021,7(3):47-50.
学,2021,24(11):1317-1324. DOI:10.12114/j.issn.1007-
GAO W J,GAO Y N. The status of human Papilloma virus test
9572.2021.00.402.
in cervical cancer screening[J]. J Multidiscip Cancer Manag:
Chinese Medical Doctor Association (CMDA)'s General
Electron Version,2021,7(3):47-50.
Practitioners Sub-association,The Primary Care Branch of
[17]中国医师协会全科医师分会,北京妇产学会社区与基层分会 .
Beijing Institute of Obstetrics & Gynecology. Consensus on health
宫颈癌筛查结果异常人群社区管理专家建议[J]. 中国全科医
management in climacteric women in primary medical institutions
学,2021,24(17):2117-2121,2126. DOI:10.12114/j.issn.
edition[J].Chinese General Practice,2021,24(11):
1007-9572.2021.00.531.
1317-1324. DOI:10.12114/j.issn.1007-9572.2021.00.402.
Chinese Medical Doctor Association(CMDA)'s General
[13]BRUNI L,ALBERO G,SERRANO B,et al. ICO/IARC
Practitioners Sub-association,the Primary Care Branch of Beijing
Information Centre on HPV and Cancer (HPV Information
Institute of Obstetrics & Gynecology.Expert recommendations on
Centre). Human Papillomavirus and Related Diseases in community-based management of women with abnormal cervical
China[EB/OL]. (2019-06-17)[2020-11-25]. https://hpvcentre. cancer screening test results[J]. Chinese General Practice,
net/ statistics/reports/CHN.pdf?t = 1606722464904. 2021,24(17):2117-2121,2126. DOI:10.12114/
[14]韦梦娜,余艳琴,徐慧芳,等 . 中国大陆地区不同宫颈病变人 j.issn.1007-9572.2021.00.531.
群中人乳头瘤病毒感染率及型别分布的系统研究[J]. 中国 (收稿日期:2021-12-10;修回日期:2022-01-10)
肿瘤临床与康复,2020,27(2):133-137. DOI:10.13455/j. (本文编辑:毛亚敏)
(上接第 2222 页) from[18F]-fluorodeoxyglucose positron emission tomography/
[40]NITHYA B,ILANGO V. Evaluation of machine learning based computed tomography[J]. SSRN Journal,2019,29(12):
optimized feature selection approaches and classification methods for 6741-6749. DOI:10.2139/ssrn.3292576.
cervical cancer prediction[J]. SN Appl Sci,2019,1(6):1-16. [46]PERGIALIOTIS V,POULIAKIS A,PARTHENIS C,et al. The
DOI:10.1007/s42452-019-0645-7. utility of artificial neural networks and classification and regression
[41]WANG T,GAO T T,YANG J B,et al. Preoperative prediction of trees for the prediction of endometrial cancer in postmenopausal
pelvic lymph nodes metastasis in early-stage cervical cancer using
women[J]. Public Health,2018,164:1-6. DOI:10.1016/j.
radiomics nomogram developed based on T2-weighted MRI and
puhe.2018.07.012.
diffusion-weighted imaging[J]. Eur J Radiol,2019,114:128-
[47]ARAMENDÍA-VIDAURRETA V,CABEZA R,VILLANUEVA
135. DOI:10.1016/j.ejrad.2019.01.003.
A,et al. Ultrasound image discrimination between benign and
[42]MATSUO K,PURUSHOTHAM S,MOEINI A,et al. A pilot study
malignant adnexal masses based on a neural network approach[J].
in using deep learning to predict limited life expectancy in women
Ultrasound Med Biol,2016,42(3):742-752. DOI:10.1016/j.
with recurrent cervical cancer[J]. Am J Obstet Gynecol,2017,
ultrasmedbio.2015.11.014.
217(6):703-705. DOI:10.1016/j.ajog.2017.08.012.
[48]ACHARYA U R,SREE S V,KULSHRESHTHA S,et al.
[43]MATSUO K,PURUSHOTHAM S,JIANG B,et al. Survival
GyneScan:an improved online paradigm for screening of ovarian
outcome prediction in cervical cancer:Cox models vs deep-learning
cancer via tissue characterization[J]. Technol Cancer Res
model[J]. Am J Obstet Gynecol,2019,220(4):381.e1-
Treat,2014,13(6):529-539. DOI:10.7785/tcrtexpre
381.e4. DOI:10.1016/j.ajog.2018.12.030.
ss.2013.600273.
[44]AKAZAWA M,HASHIMOTO K. Artificial intelligence in
gynecologic cancers:current status and future challenges——a [49]ZHANG L,HUANG J,LIU L. Improved deep learning network
systematic review[J]. Artif Intell Med,2021,120:102164. based in combination with cost-sensitive learning for early detection
DOI:10.1016/j.artmed.2021.102164. of ovarian cancer in color ultrasound detecting system[J]. J Med
[45]SHEN W C,CHEN S W,WU K C,et al. Prediction of Syst,2019,43(8):251. DOI:10.1007/s10916-019-1356-8.
local relapse and distant metastasis in patients with definitive (收稿日期:2022-01-25;修回日期:2022-03-01)
chemoradiotherapy-treated cervical cancer by deep learning (本文编辑:赵跃翠)