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作 者:雷永霞[1] 李新春[1] 成程 王鹏[1] 彭玉 邓宇[1] LEI Yongxia;LI Xinchun;CHENG Cheng;WANG Peng;PENG Yu;DENG Yu(Department of Radiology,the First Affiliated Hospital of Guangzhou Medical University,Guangzhou Guangdong 510120,China)
机构地区:[1]广州医科大学附属第一医院放射科,广东广州510120
出 处:《中国继续医学教育》2022年第10期95-98,共4页China Continuing Medical Education
基 金:广州医科大学附属第一医院2020年教学类培育项目(广医附一[2020]123号)。
摘 要:目的 在对非医学影像专业住院医师的规范化培训教学中引入医学影像人工智能技术,并评价教学价值。方法 选取2019年3月—2020年8月本院非医学影像专业的60名住院医师接受规范化培训,其中30名医师纳入人工组,培训结束后根据胸部影像资料自行填写诊断报告;另30名医师纳入智能组,采用“全肺人工智能医学辅助诊断系统”阅片,在医院数字化影像和传输系统的辅助下完成诊断报告。评价两组住院医师诊断报告的完成情况。结果 智能组书写诊断报告的时间短于人工组;诊断报告质量评分高于人工组,差异有统计学意义(P <0.05)。结论 医学影像人工智能辅助教学在规范化培训教学中应用效果理想,有助于提高影像诊断效率与质量。Objective To introduce medical imaging artificial intelligence technology into the standardized training of non-medical imaging residents,and evaluate the teaching value.value.Methods From March 2019 to August 2020,60 residents of non-medical imaging specialty in our hospital were selected to receive standardized training,30 of them were included in the artificial group,and after the training,they filled in the diagnosis report according to the chest image data;the other 30 were included in the intelligent group,and they were read by the "whole lung artificial intelligence medical auxiliary diagnosis system",assisted by the hospital digital image and transmission system Complete the diagnosis report.The completion of the diagnosis reports of residents in the two groups was evaluated.Results The time of writing diagnosis report in the intelligent group was significantly shorter than that in the artificial group;the quality score of diagnosis report in the intelligent group was significantly higher than that in the artificial group,and the difference was statistically significant(P<0.05).Conclusion The application effect of medical image artificial intelligence assistant teaching in standardized training teaching is ideal,which helps to improve the efficiency and quality of image diagnosis.
关 键 词:医学影像 人工智能 非医学影像专业 住院医师 规范化培训 教学质量 教育
分 类 号:G642[文化科学—高等教育学]
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