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中华消化病与影像杂志(电子版) ›› 2021, Vol. 11 ›› Issue (01) : 20 -23. doi: 10.3877/cma.j.issn.2095-2015.2021.01.004

所属专题: 文献

全民健康助力全面小康专栏

人工智能助力健康中国建设
姚定康1, 朱樑1,()   
  1. 1. 200003 上海,海军军医大学附属长征医院内科教研室
  • 收稿日期:2020-08-15 出版日期:2021-02-01
  • 通信作者: 朱樑

Artificial intelligence promotes health construction in China

Dingkang Yao1, Liang Zhu1,()   

  1. 1. Department of Internal Medicine, Changzheng Hospital, Naval Military Medical University, Shanghai 200003, China
  • Received:2020-08-15 Published:2021-02-01
  • Corresponding author: Liang Zhu
  • About author:
    Corresponding author: Zhu Liang, Email:
引用本文:

姚定康, 朱樑. 人工智能助力健康中国建设[J/OL]. 中华消化病与影像杂志(电子版), 2021, 11(01): 20-23.

Dingkang Yao, Liang Zhu. Artificial intelligence promotes health construction in China[J/OL]. Chinese Journal of Digestion and Medical Imageology(Electronic Edition), 2021, 11(01): 20-23.

人工智能(AI)近年来发展迅猛,已经广泛应用于医疗健康领域。本文针对人工智能在新冠肺炎防控救治、肺癌及乳腺癌筛查、消化内镜图像辅助诊断等健康领域的应用进行阐述,提出人工智能助力健康中国的设想,并进行深入讨论。

Artificial intelligence(AI)has been developing rapidly in recent years.It has been widely used in the field of healthcare.This paper elaborates on the application of AI in health fields such as prevention, control and treatment of new coronavirus pneumonia(COVID-19), lung and breast cancer screening, and endoscopic image-assisted diagnosis, and puts forward the idea of AI empowering health construction in China and discusses it in depth.

1
Beam AL, Kohane IS.Big data and machine learning in health care[J].JAMA,2018,319(3): 1317-1318.
2
Rau CS, Wu SC, Chuang JF,et al.Machine learning models of survival prediction in trauma patients[J].J Clin Med,2019,8(3): 799.
3
宗淙.人工智能技术在疫情防控中的应用及发展态势研究[J].封面故事,2020,2: 30-35.
4
Wenya LB, Ahmed H, Matthew B.S,et al.Artificial intelligence in cancer imaging:Clinical challenges and applications[J].CA Cancer J Clin,2019,69(2): 127-157.
5
National Lung Screening Trial Research Team, Aberle DR, Adams AM,et al.Reduced lung-cancer mortality with low-dose computed tomographic screening[J].N Engl J Med,2011,365(5): 395-409.
6
王冠华,燕俊竹,张林.人工智能技术对肺癌早期不同密度肺结节的诊断能力探究[J].影像研究与医学应用,2020,14(4): 145-146.
7
杨锋,樊军,田周俊逸,等.人群肺亚实性结节C T筛查及人工智能应用研究初探[J].中华胸心血管外科杂志,2020,36(3): 145-150.
8
Spanhol FA, Oliverria LS, Petitjean C,et al.Breast Cancer Classification in Histopathological Images using Convolutional Neural Network[J].International Joint Conference on Neural Networks,2016,2560-2567.
9
梁翠霞,李明强,边兆英,等.基于深度学习特征的乳腺肿瘤分类模型评估[J].南方医科大学学报,2019,39(1): 89-92.
10
Daniela CL, Mihaela FA, Alexandra CF.et al.The Impact of Artificial Intelligence in the Endoscopic Assessment of Premalignant and Malignant Esophageal Lesions:Present and Future[J].Medicina, 2020,56(7): 364.
11
Horie Y, Yoshio T, Aoyama K,et al.Diagnostic outcomes of esophageal cancer by artificial intelligence using convolutional neural networks[J].Gastrointest Endosc,2019,89(1): 2532-2538.
12
Zhu Y, Wang QC, Xu MD,et al.Application of convolutional neural network in the diagnosis of the invasion depth of gastric cancer based on conventional endoscopy[J].Gastrointest Endosc,2019,89(4): 806-815.
13
Wang P, Xiao X, Glissen Brown J R,et al.Development and validation of a deep-learning algorithm for the detection of polyps during colonoscopy[J].Nature Biomedical Engineering,2018,2(10): 741-748.
14
张雅琼,栗凤霞.人工智能技术在消化内镜领域的研究现状[J].中国现代医学杂志,2020,30(8): 62-66.
15
Gulshan V, Peng L, Coram M,et al.Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs[J].JAMA,2016,316(22): 2402-2410.
16
Esteva A, Kuprel B, Novoa RA,et al.Dermatologist-level classification of skin cancer with deep neural networks[J].Nature,2017,542(7639): 115-118.
17
Li XC, Zhang S, Zhang Q,et al.Diagnosis of thyroid cancer using deep convolutional neural network models applied to sonographic images:a retrospective,multicohort,diagnostic study[J].Lancet Oncol,2019,20(2): 193-201.
18
Liang H, Tsui BY, Ni H,et al.Evaluation and accurate diagnoses of pediatric diseases using artificial intelligence[J].Nature Medicine,2019,25(3): 433-438.
19
Gutierrez Guillermo.Artificial Intelligence in the Intensive Care Unit[J].Crit Care, 2020,24: 101.
20
陈鸣,崔巍,陈瑜,等."检验医学"遇上"人工智能" [J].国际检验医学杂志,2020,41(5): 513-517.
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