[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-seo-337308-105":3,"doc-detail-337308-en":81,"detail-sidebar-cat-0-en-105":99},{"code":4,"msg":5,"data":6},0,"ok",{"site_id":7,"language":8,"slug":9,"title":10,"keywords":11,"description":12,"schema_data":13,"social_meta":74,"head_meta":76,"extra_data":78,"updated_unix":80},105,"en","the-application-of-artificial-intelligence-in-upper-gastrointestinal-cancers-review","The application of artificial intelligence in upper gastrointestinal cancers - Review","","Upper gastrointestinal cancers, mainly including esophageal cancer and gastric cancer, remain highly prevalent worldwide and are associated with low survival rates, making timely screening, precise diagnosis, appropriate treatment selection, and effective prognostic management essential. Emerging evidence indicates that artificial intelligence can support these clinical tasks. This review summarizes AI applications in four key areas—screening, diagnosis, treatment, and prognosis—covering radiomics and deep learning pipelines, disease-specific evidence for esophageal and gastric cancers, and current limitations and future research directions, including multimodal models.",{"@graph":14,"@context":73},[15,34,56],{"@type":16,"itemListElement":17},"BreadcrumbList",[18,23,27,31],{"item":19,"name":20,"@type":21,"position":22},"https://docshare.wps.com","Home","ListItem",1,{"item":24,"name":25,"@type":21,"position":26},"https://docshare.wps.com/document/","Document",2,{"item":28,"name":29,"@type":21,"position":30},"https://docshare.wps.com/document/healthcare/","Healthcare",3,{"item":32,"name":10,"@type":21,"position":33},"https://docshare.wps.com/document/the-application-of-artificial-intelligence-in-upper-gastrointestinal-cancers-review/337308/",4,{"url":32,"name":10,"@type":35,"image":36,"author":41,"headline":10,"publisher":44,"fileFormat":47,"inLanguage":8,"description":12,"dateModified":48,"datePublished":49,"encodingFormat":47,"isAccessibleForFree":50,"interactionStatistic":51},"DigitalDocument",{"url":37,"@type":38,"width":39,"height":40},"https://docshare.wps.com/thumbnails/the-application-of-artificial-intelligence-in-upper-gastrointestinal-cancers-review/337308.png","ImageObject",300,407,{"name":42,"@type":43},"Ophelia","Person",{"url":19,"name":45,"@type":46},"DocShare","Organization","application/pdf","2026-10-29","2026-09-21",true,{"@type":52,"interactionType":53,"userInteractionCount":55},"InteractionCounter",{"@type":54},"ViewAction",13,{"@type":57,"mainEntity":58},"FAQPage",[59,65,69],{"name":60,"@type":61,"acceptedAnswer":62},"Which clinical tasks are covered by artificial intelligence research for upper gastrointestinal cancers?","Question",{"text":63,"@type":64},"Research focuses on four aspects: screening, diagnosis, treatment, and prognosis.","Answer",{"name":66,"@type":61,"acceptedAnswer":67},"What methodological approaches are introduced for AI in medical image analysis?",{"text":68,"@type":64},"The review presents basic application pipelines of radiomics and deep learning for medical image analysis.",{"name":70,"@type":61,"acceptedAnswer":71},"How does the review characterize the overall burden and outcomes of upper gastrointestinal cancers?",{"text":72,"@type":64},"It highlights high incidence and mortality, poor prognosis, and strong dependence of survival on the time of cancer discovery, with substantially better outcomes when detected early.","https://schema.org",{"og:url":32,"og:type":75,"og:title":10,"og:site_name":45,"og:description":12},"article",{"robots":77,"canonical":32},"index,follow",{"doc_id":79,"site_id":7},337308,1790555354,{"code":4,"msg":82,"data":83},"success",{"doc_id":79,"user_id":84,"nickname":42,"user_avatar":85,"doc_module":4,"category_id":86,"category_name":29,"doc_title":10,"doc_description":12,"doc_content":87,"file_id":88,"file_url":89,"file_type":90,"file_size":91,"view_count":55,"is_deleted":4,"is_public":22,"is_downloadable":22,"audit_status":22,"page_count":92,"language":93,"language_code":8,"site_id":7,"html_lang":8,"table_of_contents":94,"faqs":95,"seo_title":96,"seo_description":12,"update_tm":97,"read_time":98},7971461741311,"https://ap-avatar.wpscdn.com/avatar/74000253aff267980c6?x-image-process=image/resize,m_fixed,w_180,h_180&k=1779345379180704826",7,"Journal of the National Cancer Center 5 (2025) 113–131  \nContents lists available at ScienceDirect  \nJournal of the National Cancer Center  \njournal [homepage:](homepage: www.elsevier.com/locate/jncc)[ www.elsevier.com/locate/jncc](homepage: www.elsevier.com/locate/jncc)  \n| Review\u003Cbr>The application of artificial intelligence in upper gastrointestinal cancers\u003Cbr>Xiaoying Huang1,2,†, Minghao Qin1,2,3,†, Mengjie Fang4,5,†, Zipei Wang1,2, Chaoen Hu 1,2, Tongyu Zhao1,2,6, Zhuyuan Qin7,8, Haishan Zhu9, Ling Wu9, Guowei Yu 9, Francesco De Cobelli 10, Xuebin Xie9,∗, Diego Palumbo10,∗, Jie Tian1,4,5,∗, Di Dong1,2,∗ |  |  |  | |\n| --- | --- | --- | --- | --- |\n| 1 CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China\u003Cbr>2 School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China\u003Cbr>3 University of Science and Technology Beijing, Beijing, China\u003Cbr>4 Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Beihang University, Beijing, China\u003Cbr>5 Key Laboratory of Big Data-Based Precision Medicine, Beihang University, Ministry of Industry and Information Technology, Beijing, China\u003Cbr>6 University of Science and Technology of China, Hefei, China\u003Cbr>7 Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China\u003Cbr>8 Beijing University of Chinese Medicine, Beijing, China\u003Cbr>9 KiangWu Hospital, Macau, China\u003Cbr>10 Department of Radiology, IRCCS San Raffaele Scientific Institute, Milan, Italy |  |  |  |  |\n| a r t i c l e | i n f o |  | a b s t r a c t |  |\n| Keywords:\u003Cbr>Upper gastrointestinal\u003Cbr>Artificial intelligence Radiomics Esophageal cancer Gastric cancer | cancers |  | Upper gastrointestinal cancers, mainly comprising esophageal and gastric cancers, are among the most prevalent cancers worldwide. There are many new cases of upper gastrointestinal cancers annually, and the survival rate tends to be low. Therefore, timely screening, precise diagnosis, appropriate treatment strategies, and effective prognosis are crucial for patients with upper gastrointestinal cancers. In recent years, an increasing number of studies suggest that artificial intelligence (AI) technology can effectively address clinical tasks related to upper gastrointestinal cancers. These studies mainly focus on four aspects: screening, diagnosis, treatment, and prognosis. In this review, we focus on the application of AI technology in clinical tasks related to upper gastrointestinal cancers. Firstly, the basic application pipelines of radiomics and deep learning in medical image analysis were introduced. Furthermore, we separately reviewed the application of AI technology in the aforementioned aspects for both esophageal and gastric cancers. Finally, the current limitations and challenges faced in the field of upper gastrointestinal cancers were summarized, and explorations were conducted on the selection of AI algorithms in various scenarios, the popularization of early screening, the clinical applications of AI, and large multimodal models. |  |\n\n1. Introduction  \nUpper gastrointestinal (UGI) cancers are among the most common cancers, primarily including esophageal cancer (EC) and gastric cancer (GC). According to the latest data, there were 510,716 new cases of EC and 968,350 new cases of GC worldwide in 2022, ranking 11th and 5th respectively in global cancer incidence. The geographical distribution of these cancers is uneven, with the highest incidence rates of EC in East Asia and East Africa, and the highest incidence rates of GC in East Asia, Eastern Europe, and South America.1 In the same year, there were 224,000 new cases of EC and 358,700 new cases of GC in China,2 accounting for approximately 43.86 % and 37.04 % of the global cases of these cancers, respectively. Alongside the high incidence rates, UGI cancers have high mortality rates and poor prognosis. In 2022, the number  \nof deaths worldwide due to UGI cancers was >1.1 million, with 445,129 d","cbCaiksYxHgaAf0D","https://ap.wps.com/l/cbCaiksYxHgaAf0D","pdf",2101018,19,"English","# Introduction\n# Keywords and overview\n# AI applications in screening, diagnosis, treatment, and prognosis\n## Radiomics and deep learning pipelines in medical imaging\n## Disease-specific review: esophageal cancer and gastric cancer\n# Limitations, challenges, and future directions","[{\"question\":\"Which clinical tasks are covered by artificial intelligence research for upper gastrointestinal cancers?\",\"answer\":\"Research focuses on four aspects: screening, diagnosis, treatment, and prognosis.\"},{\"question\":\"What methodological approaches are introduced for AI in medical image analysis?\",\"answer\":\"The review presents basic application pipelines of radiomics and deep learning for medical image analysis.\"},{\"question\":\"How does the review characterize the overall burden and outcomes of upper gastrointestinal cancers?\",\"answer\":\"It highlights high incidence and mortality, poor prognosis, and strong dependence of survival on the time of cancer discovery, with substantially better outcomes when detected early.\"}]","The application of artificial intelligence in upper gastrointestinal cancers - Review | PDF",1790018545,48,{"code":4,"msg":82,"data":100},[101,105,109,113,118,123,126,131,136,139,143],{"id":22,"doc_module":4,"doc_module_name":25,"category_name":102,"show_sort_weight":103,"slug":104},"Story & Novel",90,"story-novel",{"id":26,"doc_module":4,"doc_module_name":25,"category_name":106,"show_sort_weight":107,"slug":108},"Literature",80,"literature",{"id":33,"doc_module":4,"doc_module_name":25,"category_name":110,"show_sort_weight":111,"slug":112},"Exam",70,"exam",{"id":114,"doc_module":4,"doc_module_name":25,"category_name":115,"show_sort_weight":116,"slug":117},5,"Comic",60,"comic",{"id":119,"doc_module":4,"doc_module_name":25,"category_name":120,"show_sort_weight":121,"slug":122},6,"Technology",50,"technology",{"id":86,"doc_module":4,"doc_module_name":25,"category_name":29,"show_sort_weight":124,"slug":125},40,"healthcare",{"id":127,"doc_module":4,"doc_module_name":25,"category_name":128,"show_sort_weight":129,"slug":130},8,"Research & Report",30,"research-report",{"id":132,"doc_module":4,"doc_module_name":25,"category_name":133,"show_sort_weight":134,"slug":135},9,"Religion & Spirituality",20,"religion-spirituality",{"id":134,"doc_module":4,"doc_module_name":25,"category_name":137,"show_sort_weight":134,"slug":138},"World Cup","world-cup",{"id":140,"doc_module":4,"doc_module_name":25,"category_name":141,"show_sort_weight":140,"slug":142},10,"Lifestyle","lifestyle",{"id":92,"doc_module":4,"doc_module_name":25,"category_name":144,"show_sort_weight":114,"slug":145},"General","general"]