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.	應明真, 劉夙璇, 陳晰輝, 等. 變革中的醫學教育-從信息時代到人工智能. 醫學教育研究與實踐, 2018, 26(5): 721-723.
2.	國務院. 新一代人工智能發展規劃. Available from: http://www.gov.cn/zhengce/content/2017-07/20/content_5211996.htm.
3.	萬莉, 貢麗英, 吳清, 等. 人工智能在高等醫學教育中的應用前景. 中國醫學教育技術, 2018, 32(6): 607-610.
4.	柯楊. 21世紀中國醫學教育改革再定位. 北京: 北京大學醫學出版社, 2014.
5.	戚亞男. 華西百年醫學教育技術之路的啟示-西百從堅持媒介資源建設談起. 中國醫學教育技術, 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.	衛榮, 馬鋒, 侯夢薇, 等. 人工智能在醫學教育領域的應用研究. 醫學教育研究與實踐, 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.	中國人工智能機器人首次通過國家醫療執照考試. 電信網技術, 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.	劉辰. 國務院印發《新一代人工智能發展規劃》: 構筑我國人工智能發展先發優勢. 中國科技產業, 2017, (8): 78-79.
18.	高等學校人工智能創新行動計劃. 中國信息技術教育, 2018, (8): 2-5.
19.	徐靖程. 教育部印發《教育信息化2.0行動計劃》. 中小學信息技術教, 2018, (5): 4.
20.	中共中央, 中國國務院印發《中國教育現代化2035》. Available from: http://www.gov.cn/zhengce/2019-02/23/content_5367987.htm.
21.	聯合國教科文組織發布《北京共識-人工智能與教育》. 中小學信息技術教育, 2019, (10): 5.
22.	丁世彬, 張國富, 劉永鋒, 等. 美國醫學教育特點及其對我國高等醫學教育的啟示-以美國內布拉斯加大學醫學中心為例. 中國高等醫學教育, 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.	歐陽鵬, 胡弼成. 人工智能時代教育管理的變革研究. 大學教育科學, 2019, (1): 82-88, 125.
25.	李鴻浩, 段偉文, 陳蕾, 等. 醫療人工智能技術研發與應用的倫理挑戰和對策-以我國大型公立醫院為例的思考. 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.	孫洪濤, 鄭勤華. 教育大數據的核心技術, 應用現狀與發展趨勢. 遠程教育雜志, 2016, 34(5): 41-49.
28.	Masters K. Artificial intelligence in medical education. Med Teach, 2019, 41(9): 976-980.
29.	潘克明. 利用人工智能技術推進信息技術與教育教學的融合創新. 教育信息技術, 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.	劉偉. 追問人工智能: 從劍橋到北京. 北京: 科學出版社, 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.	董樂. 人工智能在教育領域的思考. 科研信息化技術與應用, 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. 應明真, 劉夙璇, 陳晰輝, 等. 變革中的醫學教育-從信息時代到人工智能. 醫學教育研究與實踐, 2018, 26(5): 721-723.
2. 國務院. 新一代人工智能發展規劃. Available from: http://www.gov.cn/zhengce/content/2017-07/20/content_5211996.htm.
3. 萬莉, 貢麗英, 吳清, 等. 人工智能在高等醫學教育中的應用前景. 中國醫學教育技術, 2018, 32(6): 607-610.
4. 柯楊. 21世紀中國醫學教育改革再定位. 北京: 北京大學醫學出版社, 2014.
5. 戚亞男. 華西百年醫學教育技術之路的啟示-西百從堅持媒介資源建設談起. 中國醫學教育技術, 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. 衛榮, 馬鋒, 侯夢薇, 等. 人工智能在醫學教育領域的應用研究. 醫學教育研究與實踐, 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. 中國人工智能機器人首次通過國家醫療執照考試. 電信網技術, 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. 劉辰. 國務院印發《新一代人工智能發展規劃》: 構筑我國人工智能發展先發優勢. 中國科技產業, 2017, (8): 78-79.
18. 高等學校人工智能創新行動計劃. 中國信息技術教育, 2018, (8): 2-5.
19. 徐靖程. 教育部印發《教育信息化2.0行動計劃》. 中小學信息技術教, 2018, (5): 4.
20. 中共中央, 中國國務院印發《中國教育現代化2035》. Available from: http://www.gov.cn/zhengce/2019-02/23/content_5367987.htm.
21. 聯合國教科文組織發布《北京共識-人工智能與教育》. 中小學信息技術教育, 2019, (10): 5.
22. 丁世彬, 張國富, 劉永鋒, 等. 美國醫學教育特點及其對我國高等醫學教育的啟示-以美國內布拉斯加大學醫學中心為例. 中國高等醫學教育, 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. 歐陽鵬, 胡弼成. 人工智能時代教育管理的變革研究. 大學教育科學, 2019, (1): 82-88, 125.
25. 李鴻浩, 段偉文, 陳蕾, 等. 醫療人工智能技術研發與應用的倫理挑戰和對策-以我國大型公立醫院為例的思考. 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. 孫洪濤, 鄭勤華. 教育大數據的核心技術, 應用現狀與發展趨勢. 遠程教育雜志, 2016, 34(5): 41-49.
28. Masters K. Artificial intelligence in medical education. Med Teach, 2019, 41(9): 976-980.
29. 潘克明. 利用人工智能技術推進信息技術與教育教學的融合創新. 教育信息技術, 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. 劉偉. 追問人工智能: 從劍橋到北京. 北京: 科學出版社, 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. 董樂. 人工智能在教育領域的思考. 科研信息化技術與應用, 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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