人工智能在医学影像专业教学中的应用探索  

Exploration and Application of Artificial Intelligence in Medical Imaging Professional Teaching

作　　者：王国杰[1] 杨思怡 谢丽丽[1] 李坤炜[1] 刘坤凤 李绍林[1] 吴庆[1] Wang Guojie;Yang Siyi;Xie Lili;Li Kunwei;Liu Kunfeng;Li Shaolin;Wu Qing(The Fifth Affiliated Hospital of Sun Yat-sen University,Zhuhai 519000,Guangdong,China;Donghua Hospital of Dongguan,Dongguan 523000,Guangdong,China;Cancer Hospital Affiliated to Sun Yat-sen University,Guangzhou 510000,Guangdong,China)

机构地区：[1]中山大学附属第五医院,广东珠海519000 [2]东莞市东华医院,广东东莞523000 [3]中山大学附属肿瘤医院,广东广州510000

出　　处：《中国高等医学教育》2024年第2期13-14,共2页China Higher Medical Education

基　　金：广东省高等教育学会“十三五”规划高校青年教师高等教育学研究课题(19GYB028);中山大学附属第五医院2019年校级本科教学质量工程类项目;中山大学附属第五医院2021年校级本科教学质量工程类项目;广东省本科高校教学质量与教学改革工程建设项目(2021-29)。

摘　　要：目的:探讨人工智能结合传统教学方法在医学影像专业实习教学中的应用效果。方法:选取医学影像学专业实习生18人,分为两组,每组9人,对照组接受传统教学模式,试验组接受人工智能辅助诊断系统结合传统教学模式,比较两组肺结节定位诊断水平。结果:试验组肺结节定位诊断考核成绩明显高于对照组。结论:人工智能辅助诊断系统结合传统教学模式能够显著提高影像诊断教学水平。Objective:To explore the application effect of artificial intelligence combined with traditional teaching methods in practical teaching of medical imaging major.Methods:18 medical imaging professional interns were selected and divided into two groups,with 9 people in each group.They received the traditional teaching model(control group)and the artificial intelligence-assisted diagnosis system combined with the traditional teaching model(experimental group)respectively.The two groups were compared.Nodule localization diagnostic level.Results:The test group's pulmonary nodule localization diagnosis assessment scores were significantly higher than those of the control group.Conclusion:The artificial intelligence-assisted diagnosis system combined with the traditional teaching model can significantly improve the level of imaging diagnosis teaching.

关 键 词：人工智能 医学影像 教学 

分 类 号：G642[文化科学—高等教育学]