Abstract：Since it is challenging to build high quality datasets with strict requirement on diversity, capacity and standardization,
testing methods based on testsets are not feasible for all intended uses. As supplement, simulated data may provide useful extension
to regular testsets. In this study, we performed mathematical and physical transform on current data for testing and observed the
corresponding changes of AI output. Results showed that the sensitivity and specificity of different algorithms under test showed
significant difference after image compression, image cropping and filtering. In this paper, simulated data was used in the evaluation
of representative algorithms as an initial attempt, which demonstrated that the value of such a method could reflect the performance
of AI from a new perspective, and facilitate the evaluation of generalization ability.
孟祥峰，王浩，张超，任海萍. 糖尿病视网膜病变AI产品的模拟对抗测试研究[J]. 中国医疗设备, 2018, 33(12): 18-21.
MENG Xiangfeng, WANG Hao, ZHANG Chao, REN Haiping. Study on Testing of AI Products for Diabetic Retinopathy by Simulated Data. China Medical Devices, 2018, 33(12): 18-21.