In the context of the rapid development of artificial intelligence, the education of medical imaging technology faces new opportunities and challenges. At present, there are some problems in the teaching of linear algebra courses, such as the disconnection between the teaching content and the professional needs, the emphasis on theory, and the low interest of students in learning. Taking the linear algebra course of the four-year medical imaging technology major at Capital Medical University as an example, this paper summarized a series of teaching reform methods based on artificial intelligence. By building a case library, introducing Python programming, animations and interactive web pages, and combining them with the blended teaching mode, the ways of integrating artificial intelligence technology into the construction of the linear algebra course in medical imaging technology were explored.
1.教育部高等学校教学指导委员会. 普通高等学校本科专业类教学质量国家标准[M]. 北京: 高等教育出版社, 2018: 753.
2.Rajpurkar P, Lungren MP. The current and future state of AI interpretation of medical images[J]. N Engl J Med, 2023, 388(21): 1981-1990. DOI: 10.1056/NEJMra301725.
3.李青, 李润睿, 强彦, 等. 人工智能在医学CT图像重建中的研究进展[J]. 太原理工大学学报, 2023, 54(1): 1-16. [Li Q, Li RR, Qiang Y, et al. Research and progress of artificial intelligence in medical CT image reconstruction[J]. Journal of Taiyuan University of Technology, 2023, 54(1): 1-16.] DOI: 10.16355/j.cnki.issn1007-9432tyut.2023.01.001.
4.陈冲, 夏黎明. 积极稳妥地推进人工智能在医学影像的应用[J]. 中华放射学杂志, 2022, 56(1): 5-8. [Chen C, Xia LM. Promoting the application of artificial intelligence in medical imaging actively and steadily[J]. Chinese Journal of Radiology, 2022, 56(1): 5-8.] DOI: 10.3760/cma.j.cn112149-20210813-00752.
5.赵娟, 彭春花, 赵莹, 等. 以学科交叉为导向的医药类高校线性代数课程思政建设[J]. 数理医药学杂志, 2024, 37(4): 318-322. [Zhao J, Peng CH, Zhao Y, et al. The construction of curriculum ideological and political education of linear algebra courses in medical universities oriented by interdisciplinarity[J]. Journal of Mathematical Medicine, 2024, 37(4): 318-322.] DOI: 10.12173/j.issn.1004-4337.202401140.
6.李冬果, 高磊, 郑文新, 等. 基于高端复合人才培养目标探索线性代数教学改革[J]. 数理医药学杂志, 2023, 36(11): 874-880. [Li DG, Gao L, Zheng WX, et al. Exploration of linear algebra teaching reform based on the training goal of high-end composite talents[J]. Journal of Mathematical Medicine, 2023, 36(11): 874-880.] DOI: 10.12173/j.issn.1004-4337.202308075.
7.鲁晓磊,吕学斌. 大数据背景下人工智能发展对大学数学教学的启示[J]. 大学数学, 2020, 36(4): 60-67. [Lu XL, Lyu XB. The implications for mathematics teaching of artificial intelligence development based on the big data[J]. College Mathematics, 2020, 36(4): 60-67.] DOI: 10.3969/j.issn.1672-1454.2020.04.011.
8.倪丹. 人工智能元素融入大学数学课程的可行性探析[J]. 山西能源学院学报, 2021, 34(5): 30-32. [Ni D. A feasibility study on integrating artificial intelligence elements into university mathematics curriculum[J]. Journal of Shanxi Coal-Mining Administrators College, 2021, 34(5): 30-32.] DOI: 10.3969/j.issn.1008-8881.2021.05.011.
9.沈卉卉. 大数据环境下人工智能与大学数学教育相融合的创新教学研究[J]. 高等数学研究, 2019, 22(4): 113-116, 125. [Shen HH. On combination of mathematics and artificial intelligence for teaching in big data environment[J]. Studies in College Mathematics, 2019, 22(4): 113-116, 125.] DOI: 10.3969/j.issn.1008-1399.2019.04.031.
10.唐宇迪, 李琳, 侯惠芳, 等. 人工智能数学基础[M]. 北京: 北京大学出版社, 2020.
11.李海云, 严华刚. 医学影像工程学[M]. 北京: 机械工业出版社, 2011.