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The review highlights WHO efforts to scale high-performance HPV-based screening for women aged 35–45 by 2030 and outlines the need for accurate, efficient, and effective screening strategies. It summarizes how AI, including deep learning for medical image interpretation, can enhance screening, management, and follow-up, while addressing future challenges.",{"@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-strengthens-cervical-cancer-screening-present-and-future/340350/",{"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-strengthens-cervical-cancer-screening-present-and-future/340350.png","ImageObject",300,407,{"name":92,"@type":93},"Eden","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-22","2026-09-22",true,{"@type":102,"interactionType":103,"userInteractionCount":39},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"Why is cervical cancer screening a priority in global health?","Question",{"text":112,"@type":113},"Cervical cancer causes substantial mortality worldwide and has a long premalignant phase, making it preventable through primary and secondary prevention. Implementation challenges, including inadequate infrastructure and suboptimal sensitivity of current tests, limit progress in many countries.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"What screening approach does WHO recommend and why?",{"text":117,"@type":113},"WHO recommends HPV detection-based primary screening because it is more sensitive and objective than cytology. Cytology triage for HPV-positive women and alternative triage methods are discussed as strategies that depend on available resources and expertise.",{"name":119,"@type":110,"acceptedAnswer":120},"How can AI support cervical cancer screening now and in the future?",{"text":121,"@type":113},"AI and deep learning can provide automated, objective, and unbiased interpretation of medical images, supporting detection of abnormal cytology and cervical neoplastic diseases. The review also emphasizes that future deployment will face technical and practical challenges.","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},340350,1790629687,{"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":39,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":139,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":144,"read_time":36},1374391974468,"https://ap-avatar.wpscdn.com/davatar_29158cc5080c5b710cf443261637dec0","Cancer Biol Med 2024. doi: 10.20892/j.issn.2095-3941.2024.0198  \nREVIEW  \nArtificial intelligence strengthens cervical cancer screening – present and future  \nTong Wu1, Eric Lucas2, Fanghui Zhao3, Partha Basu2, Youlin Qiao1  \n1School of Population Medicine and Public Health, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China; 2 Early Detection, Prevention & Infections Branch International Agency for Research on Cancer (WHO), 25 avenue Tony Garnier, Lyon 69007, France; 3 Department of Cancer Epidemiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China  \n\n| ABSTRACT | Cervical cancer is a severe threat to women’s health. The majority of cervical cancer cases occur in developing countries. The |\n| --- | --- |\n| KEYWORDS | WHO has proposed screening 70% of women with high-performance tests between 35 and 45 years of age by 2030 to accelerate the elimination of cervical cancer. Due to an inadequate health infrastructure and organized screening strategy, most low-and middleincome countries are still far from achieving this goal. As part of the efforts to increase performance of cervical cancer screening, it is necessary to investigate the most accurate, efficient, and effective methods and strategies. Artificial intelligence (AI) is rapidly expanding its application in cancer screening and diagnosis and deep learning algorithms have offered human-like interpretation capabilities on various medical images. AI will soon have a more significant role in improving the implementation of cervical cancer screening, management, and follow-up. This review aims to report the state of AI with respect to cervical cancer screening. We discuss the primary AI applications and development of AI technology for image recognition applied to detection of abnormal cytology and cervical neoplastic diseases, as well as the challenges that we anticipate in the future.\u003Cbr>Cervical cancer screening; artificial intelligence; deep learning algorithms |\n\nIntroduction  \nCervical cancer remains a major cause of mortality among women with > 662,000 new cases diagnosed and approximately 349,000 deaths reported globally in 20221. The long premalignant phase of cervical cancer and the natural progression of the disease make cervical cancer the only cancer that is currently preventable through primary and secondary prevention2. The World Health Organization (WHO) has launched a global strategy to eliminate cervical cancer by the end of the millennium that includes vaccination against human papillomavirus (HPV), screening of women  \nCorrespondence to: Youlin Qiao and Partha Basu  \nE-mail: [qiaoy@cicams.ac.cn](qiaoy@cicams.ac.cn) and [basup@iarc.who.int](basup@iarc.who.int)  \nORCID ID: [https://orcid.org/0000-0001-6380-0871](https://orcid.org/0000-0001-6380-0871)  \nand [https://orcid.org/0000-0003-0124-4050](https://orcid.org/0000-0003-0124-4050)  \nReceived May 30, 2024; accepted August 12, 2024;  \npublished online September 19, 2024. Available [at www.cancerbiomed.org](at www.cancerbiomed.org)  \n©2024 The Authors. Creative Commons Attribution-NonCommercial 4.0 International License  \nusing high-performance testing, early diagnosis, and timely treatment of high-grade cervical intraepithelial neoplasia (CIN 2/3) and cancer. Cervical cytology has been widely used for cervical cancer screening but global implementation poses several challenges and suboptimal sensitivity of the test necessitates frequent screening. The WHO has recommended HPV detection-based tests for primary screening due to the higher sensitivity and objective nature of the test. While cytology triage of HPV-positive women to colposcopy before confirmation of abnormal cervical cytology serves as an effective primary approach in high-income countries, deploying this strategy requires a well-organized infrastructure and the expertise of pro","cbCaipjJSQIJIkos","https://ap.wps.com/l/cbCaipjJSQIJIkos","pdf",719294,16,"English","# Introduction\n## Global burden and prevention framework\n## Screening strategies and implementation challenges\n# Role of artificial intelligence\n## Historical development of AI in medicine\n## Deep learning and image recognition in diagnosis","[{\"question\":\"Why is cervical cancer screening a priority in global health?\",\"answer\":\"Cervical cancer causes substantial mortality worldwide and has a long premalignant phase, making it preventable through primary and secondary prevention. Implementation challenges, including inadequate infrastructure and suboptimal sensitivity of current tests, limit progress in many countries.\"},{\"question\":\"What screening approach does WHO recommend and why?\",\"answer\":\"WHO recommends HPV detection-based primary screening because it is more sensitive and objective than cytology. Cytology triage for HPV-positive women and alternative triage methods are discussed as strategies that depend on available resources and expertise.\"},{\"question\":\"How can AI support cervical cancer screening now and in the future?\",\"answer\":\"AI and deep learning can provide automated, objective, and unbiased interpretation of medical images, supporting detection of abnormal cytology and cervical neoplastic diseases. The review also emphasizes that future deployment will face technical and practical challenges.\"}]","Artificial intelligence strengthens cervical cancer screening - present and future | PDF",1790035953]