{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,27]],"date-time":"2026-10-27T23:33:57Z","timestamp":1793144037668,"version":"4.5.0"},"reference-count":37,"publisher":"Wiley","issue":"18","license":[{"start":{"date-parts":[[2020,7,22]],"date-time":"2020-07-22T00:00:00Z","timestamp":1595376000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["81903328"],"award-info":[{"award-number":["81903328"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Cancer Medicine"],"published-print":{"date-parts":[[2020,9]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Background<\/jats:title><jats:p>Adequate cytology is limited by insufficient cytologists in a large\u2010scale cervical cancer screening. We aimed to develop an artificial intelligence (AI)\u2010assisted cytology system in cervical cancer screening program.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>We conducted a perspective cohort study within a population\u2010based cervical cancer screening program for 0.7\u00a0million women, using a validated AI\u2010assisted cytology system. For comparison, cytologists examined all slides classified by AI as abnormal and a randomly selected 10% of normal slides. Each woman with slides classified as abnormal by either AI\u2010assisted or manual reading was diagnosed by colposcopy and biopsy. The outcomes were histologically confirmed cervical intraepithelial neoplasia grade 2 or worse (CIN2+).<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Finally, we recruited 703\u00a0103 women, of whom 98\u00a0549 were independently screened by AI and manual reading. The overall agreement rate between AI and manual reading was 94.7% (95% confidential interval [CI], 94.5%\u201094.8%), and kappa was 0.92 (0.91\u20100.92). The detection rates of CIN2+ increased with the severity of cytology abnormality performed by both AI and manual reading (<jats:italic>P<\/jats:italic><jats:sub>trend<\/jats:sub>\u00a0&lt;\u00a00.001). General estimated equations showed that detection of CIN2+ among women with ASC\u2010H or HSIL by AI were significantly higher than corresponding groups classified by cytologists (for ASC\u2010H: odds ratio [OR]\u00a0=\u00a01.22, 95%CI 1.11\u20101.34, <jats:italic>P<\/jats:italic>\u00a0&lt;\u00a0.001; for HSIL: OR\u00a0=\u00a01.41, 1.28\u20101.55, <jats:italic>P<\/jats:italic>\u00a0&lt;\u00a0.001). AI\u2010assisted cytology was 5.8% (3.0%\u20108.6%) more sensitive for detection of CIN2+ than manual reading with a slight reduction in specificity.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>AI\u2010assisted cytology system could exclude most of normal cytology, and improve sensitivity with clinically equivalent specificity for detection of CIN2+ compared with manual cytology reading. Overall, the results support AI\u2010based cytology system for the primary cervical cancer screening in large\u2010scale population.<\/jats:p><\/jats:sec>","DOI":"10.1002\/cam4.3296","type":"journal-article","created":{"date-parts":[[2020,7,22]],"date-time":"2020-07-22T16:46:00Z","timestamp":1595436360000},"page":"6896-6906","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":100,"title":["The artificial intelligence\u2010assisted cytology diagnostic system in large\u2010scale cervical cancer screening: A population\u2010based cohort study of 0.7\u00a0million women"],"prefix":"10.1002","volume":"9","author":[{"given":"Heling","family":"Bao","sequence":"first","affiliation":[{"name":"Department of Maternal and Child Health School of Public Health Peking University Beijing China"},{"name":"National Center for Chronic and Non\u2010communicable Disease Control and Prevention Chinese Center for Disease Control and Prevention Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaorong","family":"Sun","sequence":"additional","affiliation":[{"name":"Landing Cloud Medical Laboratory Co. Wuhan China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yi","family":"Zhang","sequence":"additional","affiliation":[{"name":"Electronic and Information Engineering Department Wenhua College Wuhan China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Baochuan","family":"Pang","sequence":"additional","affiliation":[{"name":"Landing Artificial Intelligence Center for Pathological Diagnosis Wuhan University Wuhan China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hua","family":"Li","sequence":"additional","affiliation":[{"name":"Landing Cloud Medical Laboratory Co. Wuhan China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Liang","family":"Zhou","sequence":"additional","affiliation":[{"name":"Landing Cloud Medical Laboratory Co. Wuhan China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fengpin","family":"Wu","sequence":"additional","affiliation":[{"name":"Landing Cloud Medical Laboratory Co. Wuhan China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dehua","family":"Cao","sequence":"additional","affiliation":[{"name":"Landing Cloud Medical Laboratory Co. Wuhan China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jian","family":"Wang","sequence":"additional","affiliation":[{"name":"Landing Cloud Medical Laboratory Co. Wuhan China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6624-4070","authenticated-orcid":false,"given":"Bojana","family":"Turic","sequence":"additional","affiliation":[{"name":"Landing Cloud Medical Laboratory Co. Wuhan China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9541-3654","authenticated-orcid":false,"given":"Linhong","family":"Wang","sequence":"additional","affiliation":[{"name":"Landing Cloud Medical Laboratory Co. Wuhan China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2020,7,22]]},"reference":[{"key":"e_1_2_9_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(11)61351-2"},{"key":"e_1_2_9_3_1","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2458-12-992"},{"key":"e_1_2_9_4_1","doi-asserted-by":"publisher","DOI":"10.1002\/ijc.31806"},{"key":"e_1_2_9_5_1","doi-asserted-by":"publisher","DOI":"10.1136\/bmj.j504"},{"key":"e_1_2_9_6_1","doi-asserted-by":"publisher","DOI":"10.1001\/jama.2018.10897"},{"key":"e_1_2_9_7_1","doi-asserted-by":"publisher","DOI":"10.1097\/AOG.0000000000001708"},{"key":"e_1_2_9_8_1","doi-asserted-by":"publisher","DOI":"10.3322\/caac.21392"},{"key":"e_1_2_9_9_1","doi-asserted-by":"publisher","DOI":"10.1007\/BF03404377"},{"key":"e_1_2_9_10_1","doi-asserted-by":"publisher","DOI":"10.1002\/ijc.30926"},{"key":"e_1_2_9_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(09)61394-5"},{"key":"e_1_2_9_12_1","doi-asserted-by":"publisher","DOI":"10.1002\/cam4.1321"},{"key":"e_1_2_9_13_1","doi-asserted-by":"publisher","DOI":"10.1002\/dc.23931"},{"key":"e_1_2_9_14_1","doi-asserted-by":"publisher","DOI":"10.1016\/S1470-2045(10)70264-3"},{"key":"e_1_2_9_15_1","doi-asserted-by":"publisher","DOI":"10.1136\/bmj.39196.740995.BE"},{"key":"e_1_2_9_16_1","first-page":"3518","article-title":"Application of deep learning to the classification of images from colposcopy","volume":"15","author":"Sato M","year":"2018","journal-title":"Oncol Lett"},{"key":"e_1_2_9_17_1","doi-asserted-by":"publisher","DOI":"10.1093\/jnci\/djy225"},{"key":"e_1_2_9_18_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cmpb.2016.10.001"},{"key":"e_1_2_9_19_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2016.09.027"},{"key":"e_1_2_9_20_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.procs.2016.06.105"},{"key":"e_1_2_9_21_1","doi-asserted-by":"publisher","DOI":"10.1309\/AGB1MJ9H5N43MEGX"},{"key":"e_1_2_9_22_1","doi-asserted-by":"publisher","DOI":"10.1136\/bmj.39219.645475.55"},{"key":"e_1_2_9_23_1","doi-asserted-by":"publisher","DOI":"10.5858\/arpa.2010-0739-OA"},{"key":"e_1_2_9_24_1","doi-asserted-by":"publisher","DOI":"10.4103\/0970-9371.126659"},{"key":"e_1_2_9_25_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.canep.2017.04.011"},{"key":"e_1_2_9_26_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijgo.2009.04.003"},{"key":"e_1_2_9_27_1","first-page":"346","article-title":"Analysis of the reported data of national rural cervical cancer screening project from 2012 to 2013, China","volume":"50","author":"Luo XM","year":"2016","journal-title":"Chin J Prev Med"},{"key":"e_1_2_9_28_1","first-page":"84","article-title":"Hr\u2010HPV testing in the management of women with ASC\u2010US+ and in the follow\u2010up of women with cytological abnormalities and negative colposcopy. 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