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人工智能在消化内镜中的应用与前景

Application and prospect of artificial intelligence in digestive endoscopy.

作者信息

Zhuang Huangming, Bao Anyu, Tan Yulin, Wang Hanyu, Xie Qingfang, Qiu Meiqi, Xiong Wanli, Liao Fei

机构信息

Gastroenterology Department, Renmin Hospital of Wuhan University, Wuhan, Hubei, China.

Clinical Laboratory, Renmin Hospital of Wuhan University, Wuhan, Hubei, China.

出版信息

Expert Rev Gastroenterol Hepatol. 2022 Jan;16(1):21-31. doi: 10.1080/17474124.2022.2020646. Epub 2021 Dec 27.

DOI:10.1080/17474124.2022.2020646
PMID:34937459
Abstract

INTRODUCTION

With the progress of science and technology, artificial intelligence represented by deep learning has gradually begun to be applied in the medical field. Artificial intelligence has been applied to benign gastrointestinal lesions, tumors, early cancer, inflammatory bowel disease, gallbladder, pancreas, and other diseases. This review summarizes the latest research results on artificial intelligence in digestive endoscopy and discusses the prospect of artificial intelligence in digestive system diseases.

AREAS COVERED

We retrieved relevant documents on artificial intelligence in digestive tract diseases from PubMed and Medline. This review elaborates on the knowledge of computer-aided diagnosis in digestive endoscopy.

EXPERT OPINION

Artificial intelligence significantly improves diagnostic accuracy, reduces physicians' workload, and provides a shred of evidence for clinical diagnosis and treatment. Shortly, artificial intelligence will have high application value in the field of medicine.

摘要

引言

随着科学技术的进步,以深度学习为代表的人工智能已逐渐开始应用于医学领域。人工智能已应用于良性胃肠道病变、肿瘤、早期癌症、炎症性肠病、胆囊、胰腺等疾病。本综述总结了人工智能在消化内镜领域的最新研究成果,并探讨了人工智能在消化系统疾病中的应用前景。

涵盖领域

我们从PubMed和Medline检索了有关人工智能在消化道疾病方面的相关文献。本综述阐述了消化内镜中计算机辅助诊断的知识。

专家意见

人工智能显著提高了诊断准确性,减轻了医生的工作量,并为临床诊断和治疗提供了依据。不久之后,人工智能将在医学领域具有很高的应用价值。

相似文献

1
Application and prospect of artificial intelligence in digestive endoscopy.人工智能在消化内镜中的应用与前景
Expert Rev Gastroenterol Hepatol. 2022 Jan;16(1):21-31. doi: 10.1080/17474124.2022.2020646. Epub 2021 Dec 27.
2
A systematic review on application of deep learning in digestive system image processing.深度学习在消化系统图像处理中应用的系统评价
Vis Comput. 2023;39(6):2207-2222. doi: 10.1007/s00371-021-02322-z. Epub 2021 Oct 31.
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Artificial intelligence and upper gastrointestinal endoscopy: Current status and future perspective.人工智能与上消化道内镜:现状与未来展望。
Dig Endosc. 2019 Jul;31(4):378-388. doi: 10.1111/den.13317. Epub 2019 Feb 14.
4
Application of Artificial Intelligence in Gastrointestinal Endoscopy.人工智能在胃肠内镜中的应用。
J Clin Gastroenterol. 2021 Feb 1;55(2):110-120. doi: 10.1097/MCG.0000000000001423.
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Research trends on artificial intelligence and endoscopy in digestive diseases: A bibliometric analysis from 1990 to 2022.人工智能和消化内镜在消化疾病中的研究趋势:1990 年至 2022 年的文献计量分析。
World J Gastroenterol. 2023 Jun 14;29(22):3561-3573. doi: 10.3748/wjg.v29.i22.3561.
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Artificial intelligence application in diagnostic gastrointestinal endoscopy - Deus ex machina?人工智能在诊断性胃肠内镜中的应用——是解围之神吗?
World J Gastroenterol. 2021 Aug 28;27(32):5351-5361. doi: 10.3748/wjg.v27.i32.5351.
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[Application of artificial intelligence in diagnosis of medical endoscope].[人工智能在医用内窥镜诊断中的应用]
Zhonghua Zhong Liu Za Zhi. 2018 Dec 23;40(12):890-893. doi: 10.3760/cma.j.issn.0253-3766.2018.12.003.
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Real-time artificial intelligence for detection of upper gastrointestinal cancer by endoscopy: a multicentre, case-control, diagnostic study.实时人工智能用于内窥镜检查上消化道癌的检测:一项多中心、病例对照、诊断研究。
Lancet Oncol. 2019 Dec;20(12):1645-1654. doi: 10.1016/S1470-2045(19)30637-0. Epub 2019 Oct 4.
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Artificial Intelligence in Digestive Endoscopy-Where Are We and Where Are We Going?消化内镜领域的人工智能——我们现在所处的位置以及未来的发展方向?
Diagnostics (Basel). 2022 Apr 8;12(4):927. doi: 10.3390/diagnostics12040927.
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Construction of a predictive model for rebleeding risk in upper gastrointestinal bleeding patients based on clinical indicators such as infection.基于感染等临床指标构建上消化道出血患者再出血风险预测模型。
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Development of machine learning-based models for predicting risk factors in acute cerebral infarction patients: a clinical retrospective study.
基于机器学习的急性脑梗死患者危险因素预测模型的构建:一项临床回顾性研究。
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A deep learning and natural language processing-based system for automatic identification and surveillance of high-risk patients undergoing upper endoscopy: A multicenter study.一种基于深度学习和自然语言处理的系统,用于对上消化道内镜检查的高危患者进行自动识别和监测:一项多中心研究。
EClinicalMedicine. 2022 Oct 31;53:101704. doi: 10.1016/j.eclinm.2022.101704. eCollection 2022 Nov.