[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-381749-105":59,"doc-detail-381749-en":130},{"code":4,"msg":5,"data":6},0,"success",[7,13,18,23,28,33,38,43,48,51,55],{"id":8,"doc_module":4,"doc_module_name":9,"category_name":10,"show_sort_weight":11,"slug":12},1,"Document","Story & Novel",90,"story-novel",{"id":14,"doc_module":4,"doc_module_name":9,"category_name":15,"show_sort_weight":16,"slug":17},2,"Literature",80,"literature",{"id":19,"doc_module":4,"doc_module_name":9,"category_name":20,"show_sort_weight":21,"slug":22},4,"Exam",70,"exam",{"id":24,"doc_module":4,"doc_module_name":9,"category_name":25,"show_sort_weight":26,"slug":27},5,"Comic",60,"comic",{"id":29,"doc_module":4,"doc_module_name":9,"category_name":30,"show_sort_weight":31,"slug":32},6,"Technology",50,"technology",{"id":34,"doc_module":4,"doc_module_name":9,"category_name":35,"show_sort_weight":36,"slug":37},7,"Healthcare",40,"healthcare",{"id":39,"doc_module":4,"doc_module_name":9,"category_name":40,"show_sort_weight":41,"slug":42},8,"Research & Report",30,"research-report",{"id":44,"doc_module":4,"doc_module_name":9,"category_name":45,"show_sort_weight":46,"slug":47},9,"Religion & Spirituality",20,"religion-spirituality",{"id":46,"doc_module":4,"doc_module_name":9,"category_name":49,"show_sort_weight":46,"slug":50},"World Cup","world-cup",{"id":52,"doc_module":4,"doc_module_name":9,"category_name":53,"show_sort_weight":52,"slug":54},10,"Lifestyle","lifestyle",{"id":56,"doc_module":4,"doc_module_name":9,"category_name":57,"show_sort_weight":24,"slug":58},19,"General","general",{"code":4,"msg":60,"data":61},"ok",{"site_id":62,"language":63,"slug":64,"title":65,"keywords":66,"description":67,"schema_data":68,"social_meta":123,"head_meta":125,"extra_data":127,"updated_unix":129},105,"en","artificial-intelligence-and-visual-inspection-in-cervical-cancer-screening","Artificial intelligence and visual inspection in cervical cancer screening","","Visual inspection with acetic acid (VIA) for cervical cancer screening is limited by human subjectivity and insufficient skilled personnel. A diagnostic study evaluated a decision support system powered by artificial intelligence alongside healthcare workers and visual inspection experts. Using 83 images from existing datasets with expert consensus as the reference, performance was assessed by sensitivity, specificity, area under the curve, and intra- and inter-observer agreement via Fleiss kappa.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":35,"@type":76,"position":81},"https://docshare.wps.com/document/healthcare/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/artificial-intelligence-and-visual-inspection-in-cervical-cancer-screening/381749/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/artificial-intelligence-and-visual-inspection-in-cervical-cancer-screening/381749.png","ImageObject",300,407,{"name":92,"@type":93},"Dipper","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-25","2026-09-24",true,{"@type":102,"interactionType":103,"userInteractionCount":34},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What problem does the study address in VIA-based cervical cancer screening?","Question",{"text":112,"@type":113},"The study targets limitations of VIA, including subjectivity and a shortage of skilled human resources that can reduce diagnostic reliability.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How were the diagnostic performances of healthcare workers, experts, and the AI algorithm evaluated?",{"text":117,"@type":113},"A total of 83 images were assessed using expert consensus as the reference standard, and performance was measured with sensitivity, specificity, and area under the curve, with intra- and inter-observer agreement using Fleiss kappa.",{"name":119,"@type":110,"acceptedAnswer":120},"What reference standard did the study propose when pathology is not available?",{"text":121,"@type":113},"The conclusion states that expert consensus can serve as an alternative to histopathology to establish a reference standard for training both healthcare workers and the AI algorithm.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},381749,1790889503,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":34,"category_name":35,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":34,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":34,"language":139,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":140,"faqs":141,"seo_title":142,"seo_description":67,"update_tm":143,"read_time":144},1374404997633,"https://ap-avatar.wpscdn.com/davatar_a8503ba1806abce46bf441b54a3ca4cd","Original research  \n► Additional supplemental material is published online only. To view, please visit the journal online ([http://dx.doi.org/](http://dx.doi.org/)[ ](http://dx.doi.org/)[10.1136/ijgc-2023-004397](10.1136/ijgc-2023-004397)) .  \nFor numbered affiliations see end of article.  \nCorrespondence to  \nDr Carolyn Nakisige, Gynaecologic Oncology, Uganda Cancer Institute, Kampala, Uganda; carolyn. nakisige@ [uci.or.ug](uci.or.ug)  \nReceived 23 February 2023 Accepted 7 August 2023 Published Online First  \n4 September 2023  \n© IGCS and ESGO 2023. Re-use permitted under CC BY-NC. No commercial re-use. Published by BMJ.  \nTo cite: Nakisige C, de Fouw M, Kabukye J, et al. Int J Gynecol Cancer 2023;33:1515–1521 .  \nArtificial intelligence and visual inspection in cervical cancer screening  \nCarolyn Nakisige  ,1 Marlieke de Fouw,2 Johnblack Kabukye,3 Marat Sultanov,4 Naheed Nazrui,5 Aminur Rahman,6 Janine de Zeeuw,4 Jaap Koot,4 Arathi P Rao,7 Keerthana Prasad,8  \nGuruvare Shyamala,9 Premalatha Siddharta,10 Jelle Stekelenburg,4 Jogchum Jan Beltman11  \nABSTRACT  \nIntroduction Visual inspection with acetic acid is limited by subjectivity and a lack of skilled human resource. A decision support system based on artificial intelligence could address these limitations. We conducted a diagnostic study to assess the diagnostic performance using visual inspection with acetic acid under magnification of healthcare workers, experts, and an artificial intelligence algorithm.  \nMethods A total of 22 healthcare workers, 9  \ngynecologists/experts in visual inspection with acetic acid, and the algorithm assessed a set of 83 images from existing datasets with expert consensus as the reference. Their diagnostic performance was determined by analyzing sensitivity, specificity, and area under the curve, and intraand inter-observer agreement was measured using Fleiss kappa values.  \nResults Sensitivity, specificity, and area under the curve were, respectively, 80 .4%, 80 .5%, and 0.80 (95% CI 0.70 to 0 .90) for the healthcare workers, 81 .6%, 93 .5%, and 0.93 (95% CI 0.87 to 1.00) for the experts, and 80.0%, 83.3%, and 0.84 (95% CI 0.75 to 0 .93) for the algorithm. Kappa values for the healthcare workers, experts, and algorithm were 0 .45, 0 .68, and 0 .63, respectively. Conclusion This study enabled simultaneous assessment and demonstrated that expert consensus can be an alternative to histopathology to establish a reference standard for further training of healthcare workers and the artificial intelligence algorithm to improve diagnostic accuracy.  \nINTRODUCTION  \nThe WHO global strategy to accelerate the elimination of cervical cancer addressed targets that must be met by 2030. The strategy aims to upscale vaccination, screening, and treatment of cervical pre-cancer and cancer.1 Only 41% of low-income countries administer the human papillomavirus (HPV) vaccine as part of their immunization program, yet these countries suffer from the highest burden of cervical cancer morbidity and mortality.2 Therefore, screening and treatment of pre-cancer remain top priorities. In limited resource settings, visual inspection with acetic acid (VIA) is the most common screening method. It is relatively simple to use, cheap, and allows screening and treatment in one visit.3–5  \nScreening programs based on VIA need a functioning healthcare infrastructure and well-trained  \nWHAT IS ALREADY KNOWN ON THIS TOPIC  \n\n| ⇒ Visual inspection with acetic acid is limited by subjectivity and a lack of skilled human resource. Artificial intelligence has been applied to improve diagnostic accuracy.\u003Cbr>WHAT THIS STUDY ADDS. |\n| --- |\n| ⇒ In the absence of pathology, expert opinion can be used as a reference in training the artificial intelligence algorithm for cervical cancer screening in low- and middle-income countries. The algorithm has the potential to provide quality and objective decisional support in screening for cervical cancer in low resource settings.\u003Cbr>HOW THIS STUDY","cbCaifNAro3lMwGV","https://ap.wps.com/l/cbCaifNAro3lMwGV","pdf",610236,"English","# Abstract\n## Introduction\n## Methods\n## Results\n## Conclusion\n# What is already known on this topic\n# What this study adds\n# How this study might affect research, practice or policy","[{\"question\":\"What problem does the study address in VIA-based cervical cancer screening?\",\"answer\":\"The study targets limitations of VIA, including subjectivity and a shortage of skilled human resources that can reduce diagnostic reliability.\"},{\"question\":\"How were the diagnostic performances of healthcare workers, experts, and the AI algorithm evaluated?\",\"answer\":\"A total of 83 images were assessed using expert consensus as the reference standard, and performance was measured with sensitivity, specificity, and area under the curve, with intra- and inter-observer agreement using Fleiss kappa.\"},{\"question\":\"What reference standard did the study propose when pathology is not available?\",\"answer\":\"The conclusion states that expert consensus can serve as an alternative to histopathology to establish a reference standard for training both healthcare workers and the AI algorithm.\"}]","Artificial intelligence and visual inspection in cervical cancer screening | PDF",1790246878,18]