Application of an automatic blood cell morphology recognition system in blood cell morphology internship teaching for undergraduate students majoring in medical laboratory technology

doi:10.3760/cma.j.cn115259-20231125-00529

Abstract

Abstract: Objective To evaluate the application effect of an automatic blood cell morphology recognition system in the internship teaching of blood cell morphology for undergraduate students majoring in medical laboratory technology. Methods From November 2022 to October 2023, a controlled trial was conducted with 63 students from three medical colleges, who were interning in the Department of Clinical Laboratory, The Third Medical Center of Chinese PLA General Hospital. Students were randomly divided into experimental group (n=31) and control group (n=32). The experimental group received instruction with the aid of an automatic blood cell morphology recognition system, while the control group used traditional microscope-assisted teaching methods. Upon completion of the teaching sessions, both groups underwent blood cell morphology recognition tests and teaching method satisfaction surveys. Relevant data were statistically analyzed using t-tests and χ² tests. Results The experimental group scored significantly higher (78.87±6.55) compared to the control group (73.06±7.94) in blood cell morphology recognition tests. Additionally, the experimental group rated the innovativeness of the teaching method, richness of teaching resources, interest in the teaching method, interaction during teaching, convenience of post-class review, and reinforcement of basic knowledge higher with scores of (4.10±0.65), (4.10±0.70), (3.32±0.65), (3.87±0.72), (4.06±0.68), and (3.94±0.57) respectively, compared to the control group's scores of (2.91±0.69), (3.16±0.63), (2.75±0.80), (3.03±0.60), (2.84±0.63), and (3.06±0.67).There were statistical differences (all P<0.05). Conclusions Implementing an automatic blood cell morphology recognition system in the internship teaching for undergraduate students in medical laboratory technology significantly enhances the quality of blood cell morphology education and increases students' satisfaction.

Key words: Teaching, Medical laboratory technology, Automatic blood cell morphology recognition system, Undergraduates, Internship

CLC Number:

Sun Tao, Wang Yufei, Zhang Dandan, Song Lijie. Application of an automatic blood cell morphology recognition system in blood cell morphology internship teaching for undergraduate students majoring in medical laboratory technology[J]. Chinese Journal of Medical Education, 2024, 44(11): 843-847.

References

[1] 林桢, 夏少梅, 周强, 等. 临床血液学检验形态实验教学改革的体会和意义[J].国际检验医学杂志,2020,41(5):636-638. DOI: 10.3969/j.issn.1673-4130.2020.05.029.
[2] 刘贵建, 庞博. 应促进和拓展人工智能辅助血细胞形态学检查的临床应用[J].中华检验医学杂志,2023,46(3):231-237. DOI: 10.3760/cma.j.cn114452-20230213-00088.
[3] 丁红梅, 臧晓陵, 赵中建, 等. 医学检验专业临检血液形态学教学改进的探讨[J].国际检验医学杂志,2019,40(10):1264-1266. DOI: 10.3969/j.issn.1673-4130.2019.10.028.
[4] 刁渴珂, 单岩, 黄艺嘉, 等. 人工智能在医学教育应用中的伦理学问题分析[J].医学教育管理,2023,9(1):122-126. DOI: 10.3969/j.issn.2096-045X.2023.01.022.
[5] 常颜信, 钱尤雯. 人工智能在病理学教学中的应用[J].中国继续医学教育,2021,13(11):88-91. DOI: 10.3969/j.issn.1674-9308.2021.11.024.
[6] 郑晓博, 张中伟. 人工智能在重症医学教学中的应用展望[J].西南医科大学学报,2023,46(6):468-472. DOI: 10.3969/j.issn.2096-3351.2023.06.002.
[7] 张添辉, 刘舒珊, 曾锦梁, 等. 人工智能在放射科阅片教学中的应用现状及前景展望[J].继续医学教育,2023,37(10):153-156. DOI: 10.3969/j.issn.1004-6763.2023.10.039.
[8] 潘柏申.检验医学的发展和展望[J].中华检验医学杂志,2019,42(8):585-589. DOI: 10.3760/cma.j.issn.1009-8158.2019.08.001.
[9] Kratz A, Lee SH, Zini G, et al. Digital morphology analyzers in hematology: ICSH review and recommendations[J]. Int J Lab Hematol, 2019,41(4):437-447. DOI: 10.1111/ijlh.13042.
[10] 吴敬, 朱亚鑫, 曲波. 现代教育技术在医学教育中的应用与展望[J].中华医学教育杂志,2021,41(5):390-393. DOI: 10.3760/cma.j.cn115259-20201012-01450.
[11] 商蕾, 李晨辉, 刘雪凯. 人工智能辅助外周血有核红细胞形态学分类[J].标记免疫分析与临床,2024,31(3):534-538. DOI: 10.11748/bjmy.issn.1006-1703.2024.03.025.
[12] 李佳, 杨武晨, 彭贤贵, 等. 人工智能识别系统在骨髓细胞形态进修教学中的应用研究[J].卫生职业教育,2021,39(20):86-88.
[13] Li J, Ouyang J, Liu J, et al. Artificial intelligence-based online platform assists blood cell morphology learning: a mixed-methods sequential explanatory designed research[J]. Med Teach, 2023,45(6):596-603. DOI: 10.1080/0142159X.2023.2190483.
[14] 肖继刚, 王慧君, 蔡文宇, 等. 人工智能辅助骨髓细胞形态学分析在急性髓系白血病诊疗中的应用[J].中华检验医学杂志,2023,46(3):274-279. DOI: 10.3760/cma.j.cn114452-20220928-00563.
[15] 刘梅, 高占玺, 韦美萍, 等. 人工智能细胞图像分析技术可提高骨髓细胞初筛准确度[J].中华检验医学杂志,2023,46(3):286-294. DOI: 10.3760/cma.j.cn114452-20220929-00570.
[16] 蒋浩琴, 陈葳, 何军, 等. 基于人工智能的血细胞形态分析仪白细胞分类性能的多中心研究[J].中华检验医学杂志,2023,46(3):265-273. DOI: 10.3760/cma.j.cn114452-20221019-00608.
[17] 白求恩精神研究会检验医学分会, 中华医学会检验医学分会血液体液学组, 中国医学装备协会检验医学分会基础检验设备学组. 人工智能辅助外周血细胞形态学检查的中国专家共识[J].中华检验医学杂志,2023,46(3):243-258. DOI: 10.3760/cma.j.cn114452-20221206-00718.
[18] 张时民. 医学检验领域人工智能技术应用与展望[J].国际检验医学杂志,2018,39(5):513-516,520. DOI: 10.3969/j.issn.1673-4130.2018.05.001.
[19] 崔红花, 吕丽丽, 袁帅, 等. 微课在骨髓血细胞形态学教学中的应用[J].中国实验诊断学,2019,23(7):1290-1291. DOI: 10.3969/j.issn.1007-4287.2019.07.065.
[20] 林梅双, 邓聪, 邓小燕, 等. HTML5互动网页在骨髓细胞形态教学中的应用[J].国际检验医学杂志,2019,40(5):632-635. DOI: 10.3969/j.issn.1673-4130.2019.05.034.
[21] 王敏, 谭永顺, 贾守强, 等. 微信平台与演讲式教学法在骨髓细胞形态学检验实习教学中的应用[J].国际检验医学杂志,2020,41(16):2038-2041. DOI: 10.3969/j.issn.1673-4130.2020.16.029.
[22] 高蕾, 彭贤贵, 杨武晨, 等. 应用人工智能图像教学系统提高医学生骨髓细胞形态判读能力[J].中华医学教育探索杂志,2020,19(5):569-573. DOI: 10.3760/cma.j.cn116021-20190614-00129.