Artificial intelligence promotes health construction in China

doi:10.3877/cma.j.issn.2095-2015.2021.01.004

Abstract

Abstract:

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.

Key words: Artificial intelligence, Machine learning, Neural networks, Health

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

/ / Recommend

Add to citation manager EndNote|Ris|BibTeX

URL: https://zhxhbyyxzz.cma-cmc.com.cn/EN/10.3877/cma.j.issn.2095-2015.2021.01.004

https://zhxhbyyxzz.cma-cmc.com.cn/EN/Y2021/V11/I01/20

References 20

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.

[1]	Yang Li, Jinyu Cai, Xiaozhi Dang, Wanying Chang, Yan Ju, Yi Gao, Hongping Song. Application value of a deep learning-based model for generating strain elastography images using breast grayscale ultrasound images [J]. Chinese Journal of Medical Ultrasound (Electronic Edition), 2024, 21(06): 563-570.
[2]	Jingwu Yang, Meijun Zhou, Yufan Chen, Sushu Li, Yanni He, Nan Cui, Hongmei Liu. Artificial intelligence ultrasound combined with quality control circle activity comprehensively improves ability of junior sonographers to assess risk of thyroid nodules [J]. Chinese Journal of Medical Ultrasound (Electronic Edition), 2024, 21(05): 522-526.
[3]	Fanying Zeng, Jie Ruan, Xinghui Liu, Guolin He. Current status of perinatal medicine advances under the new reproductive situation and coping strategies in prenatal care [J]. Chinese Journal of Obstetrics & Gynecology and Pediatrics(Electronic Edition), 2024, 20(05): 519-524.
[4]	Li Ye, Yu Du. Application of deep learning in clinical diagnosis and treatment of pulpal and periapical diseases [J]. Chinese Journal of Stomatological Research(Electronic Edition), 2024, 18(06): 351-356.
[5]	Ranjia Liu, Xiangli Cui, Xiaozhu Zhou, Wei Qu, Zhijun Zhu. A systematic review of health-related quality of life assessment for pediatric liver transplant recipients [J]. Chinese Journal of Transplantation(Electronic Edition), 2024, 18(05): 302-309.
[6]	Ying Xiong, Jinglai Lin, Qi Bai, Jianming Guo, Shuo Wang. How far is AI from clinical application in automated renal cell carcinoma pathological diagnosis？ [J]. Chinese Journal of Endourology(Electronic Edition), 2024, 18(06): 535-540.
[7]	Wei Li, Zijian Song, Yancheng Lai, Rui Zhou, Han Wu, Longxin Deng, Rui Chen. The current state and prospects of artificial intelligence applied to prognosis prediction in prostate cancer patients [J]. Chinese Journal of Endourology(Electronic Edition), 2024, 18(06): 541-546.
[8]	Junlong Huang, Wenshuang Li, Xiaoyang Li, bolong Liu, Yilong Chen, Huiping Qiu, Xiangfu Zhou. Application of artificial intelligence model based on pelvic floor ultrasound for the diagnosis of female stress urinary incontinence [J]. Chinese Journal of Endourology(Electronic Edition), 2024, 18(06): 597-605.
[9]	Mingchi Wang, Leqi Liang, Yongda Liu. Association between serum lipid and nephrolithiasis based on the NHANES database [J]. Chinese Journal of Endourology(Electronic Edition), 2024, 18(05): 485-490.
[10]	Qizhou Mo, Jin Su, Jian Huang, Jianwei Li, Sining Li, Jianjun Liu. Application of intelligent pressure-controlled flexible ureteroscopic suctioning lithotripsy in upper urinary tract stones with diameter of 10-25 mm [J]. Chinese Journal of Endourology(Electronic Edition), 2024, 18(05): 497-502.
[11]	Jinwei Zhang, Yonghong Dong, Jiaxuan Wang. Analysis and comparison of disease burden and health inequality of hernias in elderly populations between China and global levels based on GBD2021 study [J]. Chinese Journal of Hernia and Abdominal Wall Surgery(Electronic Edition), 2024, 18(06): 708-716.
[12]	Yiliang Li, Yakufu Sulayiman, Maimaitiming Maimaitiaili, Abudoureyimu Kelimu. An analysis of short-term outcomes of robotic-assisted versus conventional laparoscopic esophageal hiatal hernia repair combined with nissen fundoplication [J]. Chinese Journal of Hernia and Abdominal Wall Surgery(Electronic Edition), 2024, 18(05): 512-517.
[13]	Chengyi You, Heng You, Dongfang Ye, Wen Zhang, Yu Liu, Renyu Wang, Linxi Su, Hui Gan, Zhi Xu. Establishment of a prediction model for benign and malignant pulmonary nodules based on 3D Res UNet-Faster RCNN and CT imaging features [J]. Chinese Journal of Lung Diseases(Electronic Edition), 2024, 17(05): 673-679.
[14]	Mingyuan Sun, Heng Chu, Haibin Xu, Zhe Zhang. Progress in application of artificial intelligence in diagnosis of multiple pulmonary nodules [J]. Chinese Journal of Clinicians(Electronic Edition), 2024, 18(08): 785-790.
[15]	Lina Wang, Shuxia Lyu, Yanan Li. Correlation analysis of metacognition of health anxiety between disease acceptance and fear disease progression in stroke patients with hemiplegia [J]. Chinese Journal of Cerebrovascular Diseases(Electronic Edition), 2024, 18(05): 434-440.

Please choose a citation manager

Content to export