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    • 人工智能阅片标注系统在低年资眼科医师及医学生糖尿病视网膜病变阅片培训中的应用

    陈欢,于伟泓,罗明月,陈有信,韩若安

    Journal of Chinese Physician（2021）

    Cited 0|Views5
    Abstract
    目的:评估在低年资眼科医师及医学生中使用人工智能阅片标注系统进行糖尿病视网膜病变(DR)阅片培训的效果。方法:利用研发的人工智能阅片标注系统，将520张糖尿病患者眼底图像随机分为8组，每组65张图像。以13名低年资眼科住院医师及医学生作为研究对象，每人均对8组图片进行阅片，评价每张眼底图像的DR分级，以3名高年资眼底病专业医师给出的DR分级为金标准，对分级结果准确性的灵敏度、特异度及诊断试验一致性(Q-Kappa值)进行分析，并比较13位研究对象前4次与后4次阅片Q-Kappa值平均数的差别。结果:经过8次阅片，参加阅片人员Q-Kappa值平均数由第一次的0.67提高至第八次的0.81，前4次Q-Kappa值平均数为0.77，为显著一致性，后4次Q-Kappa值平均数为0.81，为高度一致性。将13名参加阅片培训人员分为两组进行分析，组1为低年资眼科住院医师，组2为医学院医学生，经过8次阅片，组1的Q-Kappa值平均数由第一次的0.71提高至第八次的0.76，组2的Q-Kappa值平均数由第一次的0.63提高至第八次的0.84，医学生的诊断准确度从显著一致提高至高度一致。结论:利用人工智能DR阅片标注系统，可以有效地提高低年资眼科医师及医学生的DR阅片水平，能在短时间内、利用较少的阅片量达到一定阅片准确度，是一种可行的阅片培训方法。
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    Diabetic retinopathy,Fundus oculi,Artificial intelligence,Grading training
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