The Significance of the Popularization and Promotion of Artificial Intelligence Technology (AI) in the Teaching of Medical Universities

Authors

  • Ning Du The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
  • Xin Sun The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
  • Yunfeng Zhang The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China

DOI:

https://doi.org/10.61360/BoniCETR242016440704

Keywords:

Artificial intelligence, medical education, diagnosis, data analysis, ethics

Abstract

With the increasing maturity of big data capture, the application of artificial intelligence (Artificial Intelligence, AI) technology in various fields is expanding, from simple, information, digital to a more accurate and comprehensive intelligent development, which is especially reflected in the field of medical research. Medical education not only has the laws applicable to it in ordinary higher education, but also contains the special laws of medical education, which are mainly reflected in the characteristics of lifelong uninterrupted learning and the complexity of the courses learned. With the gradual promotion of AI-assisted intelligent education means, medical education has also ushered in new opportunities and challenges. The introduction of AI technology can not only greatly improve the level of medical education, but also maintain the long-term effect of students' learning. At present, AI is mainly applied in medical education to comprehensive curriculum analysis, assisted learning and learning interest and direction assessment. In the long-term development, AI technology still has great difficulties in being widely used in medical education, such as relative difficulties in practical evaluation, difficult barriers to its own technology, and many challenges in data security and medical ethics. However, we have reason to believe that in the near future, with the continuous development and improvement of science and technology, the role of AI in medical education will continue to increase, and it will play a more important role in promoting the development of medical education.

References

Turing, A. (1955). Computing machinery and intelligence. Mind, 59(236), 433–460.

Russell, S., & Norvig, P. (2018). Artificial intelligence: A modern approach. Global Edition.Harlow, United Kingdom: Pearson Education Limited, 2018, 11–28.

Guo, F. (2017). Development plan for the next generation of artificial intelligence. 2017(35). The State Council.

Liu, Q., & Liu, X. (2019). Informatization and medical teaching reform. The Journal of the PLA Hospital Management, 26(2), 183–187.

Li , Y., Kuang, S., & Gui, Q. (2018). Discussion on the application of AI in the clinical skills training of medical students. Medical Education Research and Practice, 26(06), 908–910, 992.

Wan, L., Gong, L., & Wu, Q. (2018). Application prospect of AI in higher medical education. Chinese Medical Education Technology, 32(06), 607–610.

Wei, R., Ma, F., & Hou, M. (2017). Research on AI application in the field of medical education. Research and Practice in Medical Education, 25(06), 835–838.

Roll, I., & Wylie, R. (2016). Evolution and revolution in artificial intelligence in education. International Journal of Artificial Intelligence in Education, 26(2), 582–599.

Zhao, F., Lan, L., Cao, Z., Sun, H., Yin, X., & Jin, Z. (2018). Research on the application and development status of artificial intelligence in the field of health care in china. Chinese Journal of Health Information Management, 15(03), 344–349.

Ma, S., Jin, L., & Xie, F. (2019). Progress in AI-ized tumor liquid biopsy. Chinese Experimental Diagnostics, 23(11), 2031–2034.

Tencent. (2018). Tencent led the national key research and development project to tackle AI clinical auxiliary decision technology . Baidu. https://baijiahao.baidu.com/s?id=1617544445713206876&wfr=spider&for=pc

electronic fanatic. (2019). The first 5G-based remote human surgery-a “brain pacemaker” in parkinson’s disease was successfully implanted in china. Elecfans.com. http://m.elecfans.com/article/887139.html

Hodges, B. (2018). Learning from Dorothy Vaughan: artificial intelligenceand the health professions. Med Educ., 52(01), 11–13.

Zhang, J., Perris, K., & Zheng, Q. (2015). The power of feedback. Personnel Review, 44(05), 821–822.

Li, G., Zhou, X., Sun, J., Yu, X., Yuan, H., Liu, J., & Han, Y. (2019). Review of database techniques based on machine learning. Journal of Computer Science, 2019(12), 1–33.

Zhang, X., & Wang, K. (2013). Robot-assisted technology, rehabilitation robot and intelligent AIDS . Rehabilitation in China, 28(04), 246–248.

Chen, CK. (2010). Curriculum assessment using artificial neural networkand support vector machine modeling approaches: A case study. Association for Institutional Research, 2010(29), 1–24.

Yilmaz, O. (2017). Learner centered classroom in science instruction: Providing feedback with technology integration. International Journal of Science Education, 03(02), 604–613.

Willett, T. (2010). Current status of curriculum mapping in canada and the UK. Med Educ, 42(08), 786–793.

Hewson , M. (2010). Little ml.giving feedback in medical education: Verification of recommended techniques. Gen Intern Med., 13(02), 111–116.

Downloads

Published

2024-07-25

Issue

Section

Research Articles

How to Cite

The Significance of the Popularization and Promotion of Artificial Intelligence Technology (AI) in the Teaching of Medical Universities. (2024). Contemporary Education and Teaching Research, 5(7), 523-258. https://doi.org/10.61360/BoniCETR242016440704

Similar Articles

1-10 of 223

You may also start an advanced similarity search for this article.