Status, problems and countermeasures of artificial intelligence application in medical education_Chinese Journal of Evidence-Based Medicine

Authors：

LI Honghao ¹ , CHEN Bo ² , LI Jianping ³ , LIU Wei ⁴ , REN Tianyu ⁵ , ZHENG Shangwei ¹ , XUE Wenhe ² , LIU An ⁶ , LUO Zhumei ⁷ ,  WEN Jin ¹ ,  JIN Tao ⁸

1. Institute of Hospital Management, West China Hospital, Sichuan University, Chengdu 610041, P.R. China;
2. West China School of Medicine, West China Hospital, Sichuan University, Chengdu 610041, P.R. China;
3. School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, P.R. China;
4. Human Computer Interaction and Cognitive Engineering Laboratory, Beijing University of Posts and Telecommunications, Beijing 100876, P.R. China;
5. Chengdu Artificial Intelligence Industry Association of Sichuan Province, Chengdu 610041, P.R. China;
6. Chengdu University of Information Technology, Chengdu 610225, P.R. China;
7. Department of Oncology, The Third People’s Hospital of Chengdu, Chengdu 610014, P.R. China;
8. Department of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu 610041, P.R. China;

Corresponding author：

WEN Jin, Email: huaxiwenjin@163.com; JIN Tao, Email: jintao97@163.com

Keywords：

Artificial intelligence; Medical education; Educational reform; Evidence-based medicine

DOI：

10.7507/1672-2531.201910092

Video：

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Human society has entered the age of artificial intelligence(AI). Medical practice and education are undergoing profound changes. The government strongly advocates the application of AI in the field of education and it has been incorporated into the national strategy. The integration of medical education and AI technology is changing the paradigm of modern medical education. This paper introduces the current application status of AI in medical education, and analyzes the existing problems and proposes corresponding resolutions, so as to lay a foundation for promoting the integration of medical education and AI.

Citation： LI Honghao, CHEN Bo, LI Jianping, LIU Wei, REN Tianyu, ZHENG Shangwei, XUE Wenhe, LIU An, LUO Zhumei, WEN Jin, JIN Tao. Status, problems and countermeasures of artificial intelligence application in medical education. Chinese Journal of Evidence-Based Medicine, 2020, 20(9): 1092-1097. doi: 10.7507/1672-2531.201910092 Copy

1.	应明真, 刘夙璇, 陈晰辉, 等. 变革中的医学教育-从信息时代到人工智能. 医学教育研究与实践, 2018, 26(5): 721-723.
2.	国务院. 新一代人工智能发展规划. Available from: http://www.gov.cn/zhengce/content/2017-07/20/content_5211996.htm.
3.	万莉, 贡丽英, 吴清, 等. 人工智能在高等医学教育中的应用前景. 中国医学教育技术, 2018, 32(6): 607-610.
4.	柯杨. 21世纪中国医学教育改革再定位. 北京: 北京大学医学出版社, 2014.
5.	戚亚男. 华西百年医学教育技术之路的启示-西百从坚持媒介资源建设谈起. 中国医学教育技术, 2019, 33(1): 42-46.
6.	Chan KS, Zary N. Applications and challenges of implementing artificial intelligence in medical education: integrative review. JMIR Med Educ, 2019, 5(1): e13930.
7.	Caudell TP, Summers KL, Holten J 4th, <italic>et al</italic>. Virtual patient simulator for distributed collaborative medical education. Anat Rec B New Anat, 2003, 270(1): 23-29.
8.	Alverson DC, Jr SS, Caudell TP, <italic>et al</italic>. Distributed immersive virtual reality simulation development for medical education. Med Sci Educ, 2011, 15(1): 19-30.
9.	Kononowicz AA, Woodham LA, Edelbring S, <italic>et al</italic>. Virtual patient simulations in health professions education: systematic review and meta-analysis by the digital health education collaboration. J Med Internet Res, 2019, 21(7): e14676.
10.	卫荣, 马锋, 侯梦薇, 等. 人工智能在医学教育领域的应用研究. 医学教育研究与实践, 2017, 25(6): 835-838.
11.	Digital health study physicians' motivations and requirements for adopting digital clinical tools. Available from: https://ramaonhealthcare.com/ama-survey-digital-health-study-physicians-motivations-and-requirements-for-adopting-digital-clinical-tools/.
12.	Massachusetts medical society: artificial intelligence and the future of clinical practice. Available from: http://www.massmed.org/Continuing-Education-and-Events/Online-CME/Courses/Artificial-Intelligence/Artificial-Intelligence-and-the-Future-of-Clinical-Practice/.
13.	Jiang F, Jiang Y, Zhi H, <italic>et al</italic>. Artificial intelligence in healthcare: past, present and future. Stroke Vasc Neurol, 2017, 2(4): 230-243.
14.	中国人工智能机器人首次通过国家医疗执照考试. 电信网技术, 2017, (12): 88.
15.	Pfeifer CM. A progressive three-phase innovation to medical education in the United States. Med Educ Online, 2018, 23(1): 1427988.
16.	Nasca TJ, Philibert I, Brigham T, <italic>et al</italic>. The next GME accreditation system--rationale and benefits. N Engl J Med, 2012, 366(11): 1051-1056.
17.	刘辰. 国务院印发《新一代人工智能发展规划》: 构筑我国人工智能发展先发优势. 中国科技产业, 2017, (8): 78-79.
18.	高等学校人工智能创新行动计划. 中国信息技术教育, 2018, (8): 2-5.
19.	徐靖程. 教育部印发《教育信息化2.0行动计划》. 中小学信息技术教, 2018, (5): 4.
20.	中共中央, 中国国务院印发《中国教育现代化2035》. Available from: http://www.gov.cn/zhengce/2019-02/23/content_5367987.htm.
21.	联合国教科文组织发布《北京共识-人工智能与教育》. 中小学信息技术教育, 2019, (10): 5.
22.	丁世彬, 张国富, 刘永锋, 等. 美国医学教育特点及其对我国高等医学教育的启示-以美国内布拉斯加大学医学中心为例. 中国高等医学教育, 2017, (7): 18-19.
23.	Wartman SA, Combs CD. Reimagining medical education in the sge of AI. AMA J Ethics, 2019, 21(2): E146-E152.
24.	欧阳鹏, 胡弼成. 人工智能时代教育管理的变革研究. 大学教育科学, 2019, (1): 82-88, 125.
25.	李鸿浩, 段伟文, 陈蕾, 等. 医疗人工智能技术研发与应用的伦理挑战和对策-以我国大型公立医院为例的思考. 人工智能, 2019, (4): 70-78.
26.	Zhao H, Li G, Feng W. Research on application of artificial intelligence in medical education. 2018 International Conference on Engineering Simulation and Intelligent Control (ESAIC). Available from: https://ieeexplore.ieee.xilesou.top/abstract/document/8530428.
27.	孙洪涛, 郑勤华. 教育大数据的核心技术, 应用现状与发展趋势. 远程教育杂志, 2016, 34(5): 41-49.
28.	Masters K. Artificial intelligence in medical education. Med Teach, 2019, 41(9): 976-980.
29.	潘克明. 利用人工智能技术推进信息技术与教育教学的融合创新. 教育信息技术, 2018, (Z2): 3-5.
30.	Jobin A, Ienca M, Vayena E. The global landscape of AI ethics guidelines. Nat Mach Intell, 2019, 1(9): 389-399.
31.	Colchester K, Hagras H, Alghazzawi D, <italic>et al</italic>. A survey of artificial intelligence techniques employed for adaptive educational systems within e-learning platforms. JAISCR, 2017, 7(1): 47-64.
32.	刘伟. 追问人工智能: 从剑桥到北京. 北京: 科学出版社, 2019.
33.	Kolachalama VB, Garg PS. Machine learning and medical education. Digit Med, 2018, 1: 54.
34.	Wald HS, George P, Reis SP, <italic>et al</italic>. Electronic health record training in undergraduate medical education: bridging theory to practice with curricula for empowering patient- and relationship-centered care in the computerized setting. Acad Med, 2014, 89(3): 380-386.
35.	Verghese A, Shah NH, Harrington RA. What this computer needs is a physician: humanism and artificial intelligence. JAMA, 2018, 319(1): 19-20.
36.	董乐. 人工智能在教育领域的思考. 科研信息化技术与应用, 2018, 9(2): 17-30.
37.	Wartman SA, Combs CD. Medical education must move from the information age to the age of artificial intelligence. Acad Med, 2018, 93(8): 1107-1109.
38.	Pedro F, Subosa M, Rivas A, et al. Artificial intelligence in education: challenges and opportunities for sustainable development. 2019. Available from: http://repositorio.minedu.gob.pe/handle/MINEDU/6533.

1. 应明真, 刘夙璇, 陈晰辉, 等. 变革中的医学教育-从信息时代到人工智能. 医学教育研究与实践, 2018, 26(5): 721-723.
2. 国务院. 新一代人工智能发展规划. Available from: http://www.gov.cn/zhengce/content/2017-07/20/content_5211996.htm.
3. 万莉, 贡丽英, 吴清, 等. 人工智能在高等医学教育中的应用前景. 中国医学教育技术, 2018, 32(6): 607-610.
4. 柯杨. 21世纪中国医学教育改革再定位. 北京: 北京大学医学出版社, 2014.
5. 戚亚男. 华西百年医学教育技术之路的启示-西百从坚持媒介资源建设谈起. 中国医学教育技术, 2019, 33(1): 42-46.
6. Chan KS, Zary N. Applications and challenges of implementing artificial intelligence in medical education: integrative review. JMIR Med Educ, 2019, 5(1): e13930.
7. Caudell TP, Summers KL, Holten J 4th, <italic>et al</italic>. Virtual patient simulator for distributed collaborative medical education. Anat Rec B New Anat, 2003, 270(1): 23-29.
8. Alverson DC, Jr SS, Caudell TP, <italic>et al</italic>. Distributed immersive virtual reality simulation development for medical education. Med Sci Educ, 2011, 15(1): 19-30.
9. Kononowicz AA, Woodham LA, Edelbring S, <italic>et al</italic>. Virtual patient simulations in health professions education: systematic review and meta-analysis by the digital health education collaboration. J Med Internet Res, 2019, 21(7): e14676.
10. 卫荣, 马锋, 侯梦薇, 等. 人工智能在医学教育领域的应用研究. 医学教育研究与实践, 2017, 25(6): 835-838.
11. Digital health study physicians' motivations and requirements for adopting digital clinical tools. Available from: https://ramaonhealthcare.com/ama-survey-digital-health-study-physicians-motivations-and-requirements-for-adopting-digital-clinical-tools/.
12. Massachusetts medical society: artificial intelligence and the future of clinical practice. Available from: http://www.massmed.org/Continuing-Education-and-Events/Online-CME/Courses/Artificial-Intelligence/Artificial-Intelligence-and-the-Future-of-Clinical-Practice/.
13. Jiang F, Jiang Y, Zhi H, <italic>et al</italic>. Artificial intelligence in healthcare: past, present and future. Stroke Vasc Neurol, 2017, 2(4): 230-243.
14. 中国人工智能机器人首次通过国家医疗执照考试. 电信网技术, 2017, (12): 88.
15. Pfeifer CM. A progressive three-phase innovation to medical education in the United States. Med Educ Online, 2018, 23(1): 1427988.
16. Nasca TJ, Philibert I, Brigham T, <italic>et al</italic>. The next GME accreditation system--rationale and benefits. N Engl J Med, 2012, 366(11): 1051-1056.
17. 刘辰. 国务院印发《新一代人工智能发展规划》: 构筑我国人工智能发展先发优势. 中国科技产业, 2017, (8): 78-79.
18. 高等学校人工智能创新行动计划. 中国信息技术教育, 2018, (8): 2-5.
19. 徐靖程. 教育部印发《教育信息化2.0行动计划》. 中小学信息技术教, 2018, (5): 4.
20. 中共中央, 中国国务院印发《中国教育现代化2035》. Available from: http://www.gov.cn/zhengce/2019-02/23/content_5367987.htm.
21. 联合国教科文组织发布《北京共识-人工智能与教育》. 中小学信息技术教育, 2019, (10): 5.
22. 丁世彬, 张国富, 刘永锋, 等. 美国医学教育特点及其对我国高等医学教育的启示-以美国内布拉斯加大学医学中心为例. 中国高等医学教育, 2017, (7): 18-19.
23. Wartman SA, Combs CD. Reimagining medical education in the sge of AI. AMA J Ethics, 2019, 21(2): E146-E152.
24. 欧阳鹏, 胡弼成. 人工智能时代教育管理的变革研究. 大学教育科学, 2019, (1): 82-88, 125.
25. 李鸿浩, 段伟文, 陈蕾, 等. 医疗人工智能技术研发与应用的伦理挑战和对策-以我国大型公立医院为例的思考. 人工智能, 2019, (4): 70-78.
26. Zhao H, Li G, Feng W. Research on application of artificial intelligence in medical education. 2018 International Conference on Engineering Simulation and Intelligent Control (ESAIC). Available from: https://ieeexplore.ieee.xilesou.top/abstract/document/8530428.
27. 孙洪涛, 郑勤华. 教育大数据的核心技术, 应用现状与发展趋势. 远程教育杂志, 2016, 34(5): 41-49.
28. Masters K. Artificial intelligence in medical education. Med Teach, 2019, 41(9): 976-980.
29. 潘克明. 利用人工智能技术推进信息技术与教育教学的融合创新. 教育信息技术, 2018, (Z2): 3-5.
30. Jobin A, Ienca M, Vayena E. The global landscape of AI ethics guidelines. Nat Mach Intell, 2019, 1(9): 389-399.
31. Colchester K, Hagras H, Alghazzawi D, <italic>et al</italic>. A survey of artificial intelligence techniques employed for adaptive educational systems within e-learning platforms. JAISCR, 2017, 7(1): 47-64.
32. 刘伟. 追问人工智能: 从剑桥到北京. 北京: 科学出版社, 2019.
33. Kolachalama VB, Garg PS. Machine learning and medical education. Digit Med, 2018, 1: 54.
34. Wald HS, George P, Reis SP, <italic>et al</italic>. Electronic health record training in undergraduate medical education: bridging theory to practice with curricula for empowering patient- and relationship-centered care in the computerized setting. Acad Med, 2014, 89(3): 380-386.
35. Verghese A, Shah NH, Harrington RA. What this computer needs is a physician: humanism and artificial intelligence. JAMA, 2018, 319(1): 19-20.
36. 董乐. 人工智能在教育领域的思考. 科研信息化技术与应用, 2018, 9(2): 17-30.
37. Wartman SA, Combs CD. Medical education must move from the information age to the age of artificial intelligence. Acad Med, 2018, 93(8): 1107-1109.
38. Pedro F, Subosa M, Rivas A, et al. Artificial intelligence in education: challenges and opportunities for sustainable development. 2019. Available from: http://repositorio.minedu.gob.pe/handle/MINEDU/6533.

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