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作 者:李洁[1] 罗先富 胡晓华[1] 叶靖[1] Li Jie;Luo Xianfu;Hu Xiaohua;Ye Jing(Department of Radiology,Northern Jiangsu People's Hospital,Yangzhou 225001,Jiangsu,China)
机构地区:[1]江苏省苏北人民医院影像科,江苏扬州225001
出 处:《中国毕业后医学教育》2024年第10期745-748,共4页Chinese Journal of Graduate Medical Education
摘 要:目的探讨人工智能在非影像专业放射科住院医师规范化培训(简称住培)中的应用价值。方法收集2023年4月—2023年9月在苏北人民医院放射科参加住培的非医学影像专业住院医师共70人,按专业随机分成观察组和对照组。观察组为人工智能和讲授教学相结合组,对照组为传统的讲授教学组。通过出科考试、李克特自我评估量表评分及调查满意度对比两种教学模式的效果。结果观察组出科考试成绩、李克特自我评估量表均优于对照组(P<0.05)。观察组总满意度为88.4%,对照组总满意度为59.0%,观察组满意度明显高于对照组(P<0.05)。结论放射科住培中采用人工智能技术和讲授教学相结合方法能有效增加非影像专业住院医师的影像诊断水平及对教学的满意度。Objective To evaluate the application of artificial intelligence in the standardized residency training of non-imaging specialty resident physicians in radiology.Methods A total of 70 nonimaging professional resident physicians enrolled in the study,who underwent standardized residency training in the Radiology Department of the Northern Jiangsu People's Hospital from April to September 2023,they were randomly divided into observation group and control group according to their majors,with 35 people in each group.The observation group was a combination of artificial intelligence and lecture teaching,and the control group was the traditional lecture teaching.The effects of the two teaching modes were compared through the graduation exams,Likert self-assessment scale and satisfaction survey.Results The examination scores and Likert selfassessment scale results of the observation group were better than those of the control group(P<0.05).The total satisfaction rate of the observation group was 88.4%and that of the control group was 59.0%.The satisfaction rate of observation group was significantly higher than that of the control group(P<0.05).Conclusions The application of artificial intelligence combined with lecture teaching for the standardized residency training in radiology can effectively increase the imaging diagnosis level and teaching satisfaction of non-imaging professional resident physicians.
分 类 号:G40-034[文化科学—教育学原理]
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