{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T20:17:02Z","timestamp":1790885822850,"version":"4.1.0"},"reference-count":48,"publisher":"Wiley","issue":"2","license":[{"start":{"date-parts":[[2024,12,8]],"date-time":"2024-12-08T00:00:00Z","timestamp":1733616000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"DOI":"10.13039\/501100012151","name":"Sanming Project of Medicine in Shenzen Municipality","doi-asserted-by":"publisher","award":["SZSM202211032"],"award-info":[{"award-number":["SZSM202211032"]}],"id":[{"id":"10.13039\/501100012151","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Cytopathology"],"published-print":{"date-parts":[[2025,3]]},"abstract":"<jats:title>ABSTRACT<\/jats:title><jats:sec><jats:title>Objective<\/jats:title><jats:p>This study aimed to investigate the supporting role of artificial intelligence (AI) in digital cervical cytology training.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>A total of 104 trainees completed both manual reading and AI\u2010assisted reading tests following the AI\u2010assisted digital training regimen. The interpretation scores and the testing time in different groups were compared. Also, the consistency, sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of diagnoses were further analysed through the confusion matrix and inconsistency evaluation.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>The mean interpretation scores were significantly higher in the AI\u2010assisted group compared with the manual reading group (81.97\u2009\u00b1\u200916.670 vs. 67.98\u2009\u00b1\u200921.469, <jats:italic>p<\/jats:italic>\u2009&lt;\u20090.001), accompanied by a reduction in mean interpretation time (32.13\u2009\u00b1\u200911.740\u2009min vs. 11.36\u2009\u00b1\u20094.782\u2009min, <jats:italic>p<\/jats:italic>\u2009&lt;\u20090.001). The proportion of trainees' results with complete consistence (Category O) were improved from 0.645 to 0.803 and the averaged pairwise <jats:italic>\u03ba<\/jats:italic> scores were improved from 0.535 (moderate) to 0.731 (good) with AI assistance. The number of correct answers, accuracies, sensitivities, specificities, PPV, NPV and <jats:italic>\u03ba<\/jats:italic> scores of most class\u2010specific diagnoses (NILM, Fungi, HSV, LSIL, HSIL, AIS, AC) also improved with AI assistance. Moreover, 97.8% (89\/91) of trainees reported substantial improvement in cervical cytology interpretation ability, and all participants (100%, 91\/91) expressed a strong willingness to integrate AI\u2010assisted diagnosis into their future practice.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>The utilisation of an AI\u2010assisted digital cervical cytology training platform positively impacted trainee performance and received high satisfaction and acceptance among clinicians, suggesting its potential as a valuable adjunct to medical education.<\/jats:p><\/jats:sec>","DOI":"10.1111\/cyt.13461","type":"journal-article","created":{"date-parts":[[2024,12,9]],"date-time":"2024-12-09T04:15:11Z","timestamp":1733717711000},"page":"156-164","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Integration of <scp>AI<\/scp>\u2010Assisted in Digital Cervical Cytology Training: A Comparative Study"],"prefix":"10.1111","volume":"36","author":[{"given":"Yihui","family":"Yang","sequence":"first","affiliation":[{"name":"Department of Pathology Shenzhen Maternity and Child Healthcare Hospital  Shenzhen China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dongyi","family":"Xian","sequence":"additional","affiliation":[{"name":"Medical Affairs Department Guangzhou Betrue Technology Co. 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