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人工智能在上消化道癌症检测中的应用。

Artificial intelligence for cancer detection of the upper gastrointestinal tract.

机构信息

Department of Gastroenterology, Graduate School of Institute Clinical Medicine, University of Tsukuba, Ibaraki, Japan.

Department of Gastroenterology, Cancer Institute Hospital, Japanese Foundation for Cancer Research, Tokyo, Japan.

出版信息

Dig Endosc. 2021 Jan;33(2):254-262. doi: 10.1111/den.13897. Epub 2020 Dec 28.


DOI:10.1111/den.13897
PMID:33222330
Abstract

In recent years, artificial intelligence (AI) has been found to be useful to physicians in the field of image recognition due to three elements: deep learning (that is, CNN, convolutional neural network), a high-performance computer, and a large amount of digitized data. In the field of gastrointestinal endoscopy, Japanese endoscopists have produced the world's first achievements of CNN-based AI system for detecting gastric and esophageal cancers. This study reviews papers on CNN-based AI for gastrointestinal cancers, and discusses the future of this technology in clinical practice. Employing AI-based endoscopes would enable early cancer detection. The better diagnostic abilities of AI technology may be beneficial in early gastrointestinal cancers in which endoscopists have variable diagnostic abilities and accuracy. AI coupled with the expertise of endoscopists would increase the accuracy of endoscopic diagnosis.

摘要

近年来,人工智能(AI)在图像识别领域被发现对医生很有用,这要归功于三个因素:深度学习(即 CNN、卷积神经网络)、高性能计算机和大量数字化数据。在胃肠内窥镜领域,日本内窥镜医生已经取得了基于 CNN 的 AI 系统检测胃癌和食管癌的世界首创成果。本研究综述了基于 CNN 的 AI 用于胃肠道癌症的论文,并讨论了该技术在临床实践中的未来。使用基于 AI 的内窥镜可以实现早期癌症检测。AI 技术更好的诊断能力可能有助于早期胃肠道癌症,在这些癌症中,内窥镜医生的诊断能力和准确性存在差异。将 AI 与内窥镜医生的专业知识相结合,将提高内窥镜诊断的准确性。

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[1]
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[2]
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[3]
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[4]
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Discov Oncol. 2025-8-24

[2]
Integrating artificial intelligence in healthcare: applications, challenges, and future directions.

Future Sci OA. 2025-12

[3]
Endoscopic Diagnosis of Early Gastric Cancer and High-Risk Gastritis.

Korean J Helicobacter Up Gastrointest Res. 2024-12

[4]
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BMC Surg. 2024-11-5

[5]
Gastric Cancer Detection with Ensemble Learning on Digital Pathology: Use Case of Gastric Cancer on GasHisSDB Dataset.

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[6]
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[7]
A newly developed deep learning-based system for automatic detection and classification of small bowel lesions during double-balloon enteroscopy examination.

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[8]
Deep Learning and Gastric Cancer: Systematic Review of AI-Assisted Endoscopy.

Diagnostics (Basel). 2023-12-6

[9]
Evaluation of deep learning methods for early gastric cancer detection using gastroscopic images.

Technol Health Care. 2023

[10]
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NPJ Digit Med. 2023-3-14

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