[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-336538-105":59,"doc-detail-336538-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","a-lightweight-xai-approach-to-cervical-cancer-classification","A lightweight xAI approach to cervical cancer classification","","Cervical cancer is largely caused by persistent high-risk human papillomavirus (HPV) infection transmitted through sexual contact and typically requires molecular-based analysis for detection. The burden is higher in regions with limited healthcare resources, where liquid cytology and image-based screening are used for mass testing. Diagnostic systems based on convolutional neural networks still need pathologist verification. This work applies a four-phase optimization process to build an explainable, lightweight deep-learning classifier for liquid-cytology images, achieving over 97% accuracy for four severity classes and 100% for two classes with execution times under 1 second, while reducing computational cost versus prior approaches.",{"@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/a-lightweight-xai-approach-to-cervical-cancer-classification/336538/",{"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/a-lightweight-xai-approach-to-cervical-cancer-classification/336538.png","ImageObject",300,407,{"name":92,"@type":93},"Liam","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-29","2026-09-21",true,{"@type":102,"interactionType":103,"userInteractionCount":44},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What causes cervical cancer in most cases and why is detection challenging?","Question",{"text":112,"@type":113},"Cervical cancer is caused in the vast majority of cases by human papillomavirus (HPV) through sexual contact, and detection requires specific molecular-based analysis. Incidence is much higher in areas lacking adequate healthcare resources.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"Why are explainable AI techniques needed for cervical cancer classification systems?",{"text":117,"@type":113},"Even with AI classifiers, a pathologist must verify the final diagnosis. Explainable AI highlights the most significant data regions, helping healthcare professionals assess confidence and cross-check system-selected image areas.",{"name":119,"@type":110,"acceptedAnswer":120},"What performance does the proposed lightweight xAI approach achieve?",{"text":121,"@type":113},"The optimized custom deep-learning classifier distinguishes four severity classes with accuracy over 97%. It reaches 100% for two classes, with execution times under 1 second, including final report generation, and uses lower computational cost than prior work.","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},336538,1790076026,{"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":44,"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":26},8796095461564,"https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d","Medical & Biological Engineering & Computing (2024) 62:2281–2304 [https://doi.org/10.1007/s1](https://doi.org/10.1007/s1) 1517-024-03063-6  \nA lightweight xAI approach to cervical cancer classification  \nJavier Civit-Masot1 · Francisco Luna-Perejon1 · Luis Muñoz-Saavedra1 · Manuel Domínguez-Morales1,2 · Anton Civit1,2  \nReceived: 16 May 2023 / Accepted: 24 February 2024 / Published online: 20 March 2024 © The Author(s) 2024  \nAbstract  \nCervical cancer is caused in the vast majority of cases by the human papilloma virus (HPV) through sexual contact and requires a specific molecular-based analysis to be detected. As an HPV vaccine is available, the incidence of cervical cancer is up to ten times higher in areas without adequate healthcare resources. In recent years, liquid cytology has been used to overcome these shortcomings and perform mass screening. In addition, classifiers based on convolutional neural networks can be developed to help pathologists diagnose the disease. However, these systems always require the final verification of a pathologist to make a final diagnosis. For this reason, explainable AI techniques are required to highlight the most significant data to the healthcare professional, as it can be used to determine the confidence in the results and the areas of the image used for classification (allowing the professional to point out the areas he/she thinks are most important and cross-check them against those detected by the system in order to create incremental learning systems) . In this work, a 4-phase optimization process is used to obtain a custom deep-learning classifier for distinguishing between 4 severity classes of cervical cancer with liquid-cytology images. The final classifier obtains an accuracy over 97% for 4 classes and 100% for 2 classes with execution times under 1s (including the final report generation) . Compared to previous works, the proposed classifier obtains better accuracy results with a lower computational cost.  \nKeywords Cervical cancer · Explainable AI · Deep learning · Medical imaging · Medical diagnosis aid  \n1 Introduction  \nCervical cancer is a malignant tumor of the cervix, caused in 99% of cases by persistent infection with high-risk human papilloma viruses (HPV), a widespread virus transmitted by sexual contact [1] . This is mainly observed in women under 35 years of age in countries with low HPV vaccination ratesand limited healthcare resources. HPV types can beclassified as low risk or high risk depending on their association with benign, precancerous, or cancerous lesions.  \nCervical cancer ranks fourth globally in cancers diagnosed and fourth in women’s cancer deaths, with a higher proportion of low- and middle-income countries. It is particularly present in sub-Saharan Africa [2] . In 2020, more  \nJavier Civit-Masot, Francisco Luna-Perejon, Luis Muñoz-Saavedra, Manuel Domínguez-Morales, and Anton Civit contributed equally to this work  \nB Javier Civit-Masot[mjavier@us.es](mjavier@us.es)  \nExtended author information available on the last page of the article  \nthan 600,000 new cases were diagnosed worldwide (6.5% of all female cancers) and more than 340,000 deaths related to cervical cancer were reported. In general, 84% of new cases and around 90% of deaths occur in these countries [3] . Furthermore, in high-income countries, this incidence is 7–10 times lower.  \nEarly detection of cervical cancer plays a key role in treatment and can significantly reduce the risk ofdeath;therefore, specialized laboratory equipment and pathologists are required to perform these tests. An interview with medical specialists (cardiologists and oncologists) in the United States and Germany in2016summarized that66%ofthe critical decisions they made were based on the results obtained by the pathology and laboratory medicine (PALM) services [4]. This implies that access to high-quality and timely PALM services is needed to support health care systems.  \nHowever, for example, in sub-Saharan Africa, the numb","cbCaihTBrGh8W4ep","https://ap.wps.com/l/cbCaihTBrGh8W4ep","pdf",11647341,24,"English","# Abstract\n# Keywords\n# 1 Introduction","[{\"question\":\"What causes cervical cancer in most cases and why is detection challenging?\",\"answer\":\"Cervical cancer is caused in the vast majority of cases by human papillomavirus (HPV) through sexual contact, and detection requires specific molecular-based analysis. Incidence is much higher in areas lacking adequate healthcare resources.\"},{\"question\":\"Why are explainable AI techniques needed for cervical cancer classification systems?\",\"answer\":\" Even with AI classifiers, a pathologist must verify the final diagnosis. Explainable AI highlights the most significant data regions, helping healthcare professionals assess confidence and cross-check system-selected image areas.\"},{\"question\":\"What performance does the proposed lightweight xAI approach achieve?\",\"answer\":\"The optimized custom deep-learning classifier distinguishes four severity classes with accuracy over 97%. It reaches 100% for two classes, with execution times under 1 second, including final report generation, and uses lower computational cost than prior work.\"}]","A lightweight xAI approach to cervical cancer classification | PDF",1790015504]