Current status of the application of artificial intelligence in clinical anesthesia teaching

Fu Hailong; Jiang Xin; Wang Qilong; Li Yonghua; Yuan Hongbin

doi:10.3760/cma.j.cn116021⁃20210711⁃01405

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Current status of the application of artificial intelligence in clinical anesthesia teaching

Educational Research | 更新时间：2023-10-12

- Current status of the application of artificial intelligence in clinical anesthesia teaching
- Chinese Journal of Medical Education Research Vol. 22, Issue 9, Pages: 1295-1298(2023)
- 作者机构：
  
  海军军医大学附属长征医院麻醉科，上海　200003
- 作者简介：
  
  Li Yonghua, Email: liyonghua1207@126.com
- 基金信息：
  
  Medical Innovation Research Project of Shanghai Municipal Science and Technology Commission(20Y11909500);Teaching Achievement Cultivation Project of Navy Medical University(JPY2020A11);National Defense Military Education Discipline Planning Project(JYKYD2021025);Key Teaching and Cultivation Project of The Second Affiliated Hospital of Navy Medical University(JXPY2021B03)
- DOI：10.3760/cma.j.cn116021⁃20210711⁃01405
  CLC： R-05
- Published：20 September 2023，
  
  Received：11 July 2021，
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傅海龙, 蒋鑫, 王启龙, 等. 人工智能在临床麻醉教学领域应用现状研究[J]. 中华医学教育探索杂志, 2023, 22(9): 1295-1298.

Fu Hailong, Jiang Xin, Wang Qilong, et al. Current status of the application of artificial intelligence in clinical anesthesia teaching. [J]. Chinese Journal of Medical Education Research 22(9):1295-1298(2023)
傅海龙, 蒋鑫, 王启龙, 等. 人工智能在临床麻醉教学领域应用现状研究[J]. 中华医学教育探索杂志, 2023, 22(9): 1295-1298. DOI： 10.3760/cma.j.cn116021.

Fu Hailong, Jiang Xin, Wang Qilong, et al. Current status of the application of artificial intelligence in clinical anesthesia teaching. [J]. Chinese Journal of Medical Education Research 22(9):1295-1298(2023) DOI： 10.3760/cma.j.cn116021⁃20210711⁃01405.

摘要

随着互联网技术和大数据的发展，人工智能在麻醉学领域的应用日益广泛。在临床教学领域，人工智能同样也引发教学模式、内容和评价等一系列的创新和变革。本文结合人工智能在麻醉学领域的应用现状，分析人工智能在临床麻醉教学中对教学模式、教学效果评价、教学管理及涉及伦理问题等方面可能产生的影响，为后期人工智能融入临床麻醉教学实践进行理论铺垫和前期探讨。

Abstract

With the development of Internet technology and big data

artificial intelligence has been widely used in the field of clinical anesthesia. In the field of clinical teaching

artificial intelligence has also led to a series of innovations and changes in teaching model

contents

and evaluation. With reference to the current status of the application of artificial intelligence in the field of anesthesia

this article analyzes the possible impact of artificial intelligence on teaching model

teaching effect evaluation

teaching management

and ethical issues in clinical anesthesia teaching

so as to provide a theoretical basis for integrating artificial intelligence into clinical anesthesia teaching practice in the future.

关键词

麻醉人工智能大数据临床教学

Keywords

AnesthesiaArtificial intelligenceBig dataClinical teaching

references

杨智勇，易斌，鲁开智，等. 人工智能时代的麻醉学发展[J]. 中华麻醉学杂志， 2019， 39（6）： 641-643. DOI: 10.3760http://dx.doi.org/10.3760∕cma.j.issn.0254-1416.2019.06.001.

Gambus P, Shafer SL. Artificial intelligence for everyone [J]. Anesthesiology, 2018, 128(3): 431-433. DOI: 10.1097/ALN.0000000000001984http://dx.doi.org/10.1097/ALN.0000000000001984.

王梦溪，王娜，张欣多，等. 人工智能医学教学平台的构建[J]. 中国高等医学教育， 2020， 24（3）： 46-48. DOI: 10.3969/j.issn.1002-1701.2020.03.023http://dx.doi.org/10.3969/j.issn.1002-1701.2020.03.023.

He JX, Baxter SL, Xu J, et al. The practical implementation ofartificial intelligence technologies in medicine [J]. Nat Med, 2019, 25(1): 30-36. DOI: 10.1038/s41591-018-0307-0http://dx.doi.org/10.1038/s41591-018-0307-0.

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. DOI: 10.1001/jama.2016.17216http://dx.doi.org/10.1001/jama.2016.17216.

Wang P, Xiao X, Brown JRG, et al. Development andvalidation of a deep-learning algorithm for the detection of polyps during colonoscopy [J]. Nat Biomed Eng, 2018, 2(10): 741-748. DOI: 10.1038/s41551-018-0301-3http://dx.doi.org/10.1038/s41551-018-0301-3.

Attia ZI, Kapa S, Lopez-Jimenez F, et al. Screening for cardiac contractile dysfunction using an artificial intelligence-enabledelectrocardiogram [J]. Nat Med, 2019, 25(1): 70-74. DOI: 10.1038/s41591-018-0240-2http://dx.doi.org/10.1038/s41591-018-0240-2.

Han SS, Kim MS, Lim W, et al. Classification of the clinicalimages for benign and malignant cutaneous tumors using a deeplearning algorithm [J]. J Invest Dermatol, 2018, 138(7): 1529-1538. DOI: 10.1016/j.jid.2018.01.028http://dx.doi.org/10.1016/j.jid.2018.01.028.

Alexander JC, Joshi GP. Anesthesiology, automation, and artificial intelligence [J]. Proc (Bayl Univ Med Cent), 2017, 31(1): 117-119. DOI: 10.1080/08998280.2017.1391036http://dx.doi.org/10.1080/08998280.2017.1391036.

Simpao AF, Tan JM, Lingappan AM, et al. A systematic review of near real-time and point-of-care clinical decision support in anesthesia information management systems [J]. J Clin Monit Comput, 2017, 31(5): 885-894. DOI: 10.1007/s10877-016-9921-xhttp://dx.doi.org/10.1007/s10877-016-9921-x.

李福军，由艳秋，李悦，等. 人工智能专家系统在临床麻醉教学中的应用与评价[J]. 中国医院管理， 2020， 40（8）： 73-75.

易斌，陈芋文，钟坤华，等. 人工智能在麻醉学专业硕士临床技能培训考核中的应用可行性探讨[J]. 医学教育研究与实践， 2019， 27（3）： 421-425. DOI: 10.13555/j.cnki.c.m.e.2019.03.015http://dx.doi.org/10.13555/j.cnki.c.m.e.2019.03.015.

Gruson D, Helleputte T, Rousseau P, et al. Data science, artificial intelligence,and machine learning: opportunities for laboratory medicine and the value of positive regulation [J]. Clin Biochem, 2019， 69: 1-7. DOI: 10.1016/j.clinbiochem.2019.04.013http://dx.doi.org/10.1016/j.clinbiochem.2019.04.013.

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