[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-369728-105":59,"doc-detail-369728-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-fully-annotated-pathology-slide-dataset-for-early-gastric-cancer-and-precancerous-lesions-read-online-free","A fully annotated pathology slide dataset for early gastric cancer and precancerous lesions - read online free","","A fully annotated pathology slide dataset for examining endoscopic submucosal dissection (ESD) specimens for early gastric cancer is curated to address limitations in artificial intelligence for computational pathology. The work targets interobserver variability among pathologists and the labor-intensive creation of lesion distribution maps. The dataset supports precise detection of precancerous stages, accurate quantification of lesion distribution, and improved linkage between endoscopic findings and pathological interpretation to advance precision medicine for early gastric cancer prevention and treatment.",{"@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-fully-annotated-pathology-slide-dataset-for-early-gastric-cancer-and-precancerous-lesions-read-online-free/369728/",{"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-fully-annotated-pathology-slide-dataset-for-early-gastric-cancer-and-precancerous-lesions-read-online-free/369728.png","ImageObject",300,407,{"name":92,"@type":93},"Stanford","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-11-02","2026-09-23",true,{"@type":102,"interactionType":103,"userInteractionCount":8},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"Why is a fully annotated pathology slide dataset needed for early gastric cancer?","Question",{"text":112,"@type":113},"Current AI progress is limited by the lack of comprehensive annotated pathological datasets, which restricts accurate analysis and model development for ESD specimens.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"What key challenges in ESD pathology does the dataset aim to address?",{"text":117,"@type":113},"It targets pathologists’ interobserver variability in diagnosing precancerous lesions and the extremely time-consuming manual creation of lesion distribution maps.",{"name":119,"@type":110,"acceptedAnswer":120},"How can the dataset improve clinical precision medicine?",{"text":121,"@type":113},"It enables precise detection of precancerous stages, accurate quantification of lesion distributions, and better correlation between endoscopic findings and pathological interpretations, supporting more optimal prevention and treatment strategies.","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},369728,1790184249,{"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":8,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":52,"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":129,"read_time":143},2336477552062,"https://ap-avatar.wpscdn.com/davatar_994ba38a5ba835b3df7d355c54d3ed8d","[www. nature.com/scientificdata](www. nature.com/scientificdata)  \nopEN  \nDATA DESCrIpTor  \na fully annotated pathology slide dataset for early gastric cancer and precancerous lesions  \nChunbao Wang1,2,3,8, Jiusong Ge1,8, Yi Niu1, Caixia Ding4, Yangyang Fan2, Hongyun Chang2, ZheYang2, Caihong Ran3, Xiali teng2, Xiaolin Wang2, Lianlian Wu5,6, ZeyuGao5,7 ✉ & Chen Li1 ✉  \nGastric cancer, a significant global health concern, exhibits high morbidity and mortality, especially in advanced stages. Timely diagnosis and intervention are crucial for improving patient outcomes, with Endoscopic Submucosal Dissection (ESD) playing a pivotal role in precise, minimally invasive earlystage treatments. Despite its importance, challenges include significant interobserver variability among pathologists and the intensive labor required for detailed pathological analysis of ESD specimens impede optimal outcomes. Artificial Intelligence (AI) offers promising solutions to these challenges, yet its advancement is limited by the scarcity of comprehensive, annotated pathological datasets. In this paper, we curate a fully annotated pathology slide dataset for ESD specimen examination. This dataset not only poses a challenging task for the computational pathology field but also enables precise detection of precancerous stages and accurate quantification of lesion distribution in patients with early-stage gastric lesions. Furthermore, it enhances the correlation between endoscopic findings and pathological interpretations, thereby advancing precision medicine strategies in the prevention and treatment of early gastric cancer.  \nBackground & Summary  \nGlobally, gastric cancer remains a major cause of cancer-related deaths, accounting for approximately 1 million new cases and 768,793 deaths in 20201–4. The high fatality rates are largely attributed to late-stage diagnoses. The five-year survival rate for patients diagnosed at an early stage is over 90%5, whereas it drops to 40% for those diagnosed at a late stage3,4. Early diagnostic measures, particularly endoscopic screening6, play a crucial role. Endoscopic Submucosal Dissection (ESD) is instrumental in treating early-stage gastric cancer, significantly improving survival rates7,8. ESD is instrumental in treating early-stage gastric cancer, achieving survival rates comparable to surgical intervention for appropriately selected cases. ESD offers significant advantages: it is minimally invasive, associated with lower complication rates, cost-effective, less painful, and allows for organ preservation, ultimately enhancing the patient’s quality of life.  \nDespite the significant advancements brought by ESD, the pathology examination remains the gold standard, requiring pathologists to perform detailed quantitative diagnoses on tissues resected in ESD8. However, two significant challenges beset this process. Firstly, there is considerable interobserver variability among pathologists when diagnosing precancerous lesions9, 10, which can lead to inconsistent results and potentially delay the initiation of treatment. Secondly, and most critically, the requirement for pathologists to create lesion distribution maps for precise quantitative assessments based on pathological slides is extremely time-consuming and often impractical in routine diagnostic workflows.  \n1School of Computer Science and Technology, Xi’an Jiaotong University, Xi’an, Shaanxi, 710049, China. 2Department of Pathology, The First Affiliated Hospital of Xi’an Jiaotong University, 277 West Yanta Road, Xi’an, Shaanxi, 710061, china. 3 Department of Pathology, Ngari Prefecture People’s Hospital, Ngari, Tibet, 859000, China. 4 Department of Pathology, Shaanxi Provincial Tumor Hospital, Xi’an Jiaotong University, 309 Yanta West Road, Xi’an, Shaanxi, 710061, China. 5The Early Cancer Institute, University of Cambridge, Cambridge, CB2 0XZ, UK. 6Gastroenterology Department, Renmin Hospital of Wuhan University, Wuhan, 430060, China. 7CRUK Cambridge Centre, ","cbCaiiP1Xt91mGim","https://ap.wps.com/l/cbCaiiP1Xt91mGim","pdf",4347747,"English","# Background & Summary\n## Clinical need for early diagnosis and ESD\n## Challenges in pathology examination\n## Motivation for automated lesion distribution maps\n## Computational pathology and deep learning context","[{\"question\":\"Why is a fully annotated pathology slide dataset needed for early gastric cancer?\",\"answer\":\"Current AI progress is limited by the lack of comprehensive annotated pathological datasets, which restricts accurate analysis and model development for ESD specimens.\"},{\"question\":\"What key challenges in ESD pathology does the dataset aim to address?\",\"answer\":\"It targets pathologists’ interobserver variability in diagnosing precancerous lesions and the extremely time-consuming manual creation of lesion distribution maps.\"},{\"question\":\"How can the dataset improve clinical precision medicine?\",\"answer\":\"It enables precise detection of precancerous stages, accurate quantification of lesion distributions, and better correlation between endoscopic findings and pathological interpretations, supporting more optimal prevention and treatment strategies.\"}]","A fully annotated pathology slide dataset for early gastric cancer and precancerous lesions - read online free | PDF",25]