The application of artificial intelligence in upper gastrointestinal 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 tr...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-04-01
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| Series: | Journal of the National Cancer Center |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S266700542400125X |
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| _version_ | 1849768933262884864 |
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| author | Xiaoying Huang Minghao Qin Mengjie Fang Zipei Wang Chaoen Hu Tongyu Zhao Zhuyuan Qin Haishan Zhu Ling Wu Guowei Yu Francesco De Cobelli Xuebin Xie Diego Palumbo Jie Tian Di Dong |
| author_facet | Xiaoying Huang Minghao Qin Mengjie Fang Zipei Wang Chaoen Hu Tongyu Zhao Zhuyuan Qin Haishan Zhu Ling Wu Guowei Yu Francesco De Cobelli Xuebin Xie Diego Palumbo Jie Tian Di Dong |
| author_sort | Xiaoying Huang |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-e8d78ad99bf549b8a8641102a9b049a1 |
| institution | DOAJ |
| issn | 2667-0054 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of the National Cancer Center |
| spelling | doaj-art-e8d78ad99bf549b8a8641102a9b049a12025-08-20T03:03:38ZengElsevierJournal of the National Cancer Center2667-00542025-04-015211313110.1016/j.jncc.2024.12.006The application of artificial intelligence in upper gastrointestinal cancersXiaoying Huang0Minghao Qin1Mengjie Fang2Zipei Wang3Chaoen Hu4Tongyu Zhao5Zhuyuan Qin6Haishan Zhu7Ling Wu8Guowei Yu9Francesco De Cobelli10Xuebin Xie11Diego Palumbo12Jie Tian13Di Dong14CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, ChinaCAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China; University of Science and Technology Beijing, Beijing, ChinaBeijing Advanced Innovation Center for Big Data-Based Precision Medicine, Beihang University, Beijing, China; Key Laboratory of Big Data-Based Precision Medicine, Beihang University, Ministry of Industry and Information Technology, Beijing, ChinaCAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, ChinaCAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, ChinaCAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China; University of Science and Technology of China, Hefei, ChinaBeijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China; Beijing University of Chinese Medicine, Beijing, ChinaKiangWu Hospital, Macau, ChinaKiangWu Hospital, Macau, ChinaKiangWu Hospital, Macau, ChinaDepartment of Radiology, IRCCS San Raffaele Scientific Institute, Milan, ItalyKiangWu Hospital, Macau, China; Corresponding authors.Department of Radiology, IRCCS San Raffaele Scientific Institute, Milan, Italy; Corresponding authors.CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China; Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Beihang University, Beijing, China; Key Laboratory of Big Data-Based Precision Medicine, Beihang University, Ministry of Industry and Information Technology, Beijing, China; Corresponding authors.CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China; Corresponding authors.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.http://www.sciencedirect.com/science/article/pii/S266700542400125XUpper gastrointestinal cancersArtificial intelligenceRadiomicsEsophageal cancerGastric cancer |
| spellingShingle | Xiaoying Huang Minghao Qin Mengjie Fang Zipei Wang Chaoen Hu Tongyu Zhao Zhuyuan Qin Haishan Zhu Ling Wu Guowei Yu Francesco De Cobelli Xuebin Xie Diego Palumbo Jie Tian Di Dong The application of artificial intelligence in upper gastrointestinal cancers Journal of the National Cancer Center Upper gastrointestinal cancers Artificial intelligence Radiomics Esophageal cancer Gastric cancer |
| title | The application of artificial intelligence in upper gastrointestinal cancers |
| title_full | The application of artificial intelligence in upper gastrointestinal cancers |
| title_fullStr | The application of artificial intelligence in upper gastrointestinal cancers |
| title_full_unstemmed | The application of artificial intelligence in upper gastrointestinal cancers |
| title_short | The application of artificial intelligence in upper gastrointestinal cancers |
| title_sort | application of artificial intelligence in upper gastrointestinal cancers |
| topic | Upper gastrointestinal cancers Artificial intelligence Radiomics Esophageal cancer Gastric cancer |
| url | http://www.sciencedirect.com/science/article/pii/S266700542400125X |
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