Author: Liu, Yuliang; Zhang, Quan; Zhao, Geng; Liu, Guohua; Liu, Zhiang
Title: Deep Learning-Based Method of Diagnosing Hyperlipidemia and Providing Diagnostic Markers Automatically Document date: 2020_3_11
ID: 1r4gm2d4_34
Snippet: The model achieved a 94% ACC performance in the test set. From the training images, we could find that the performance of the model on the training set is similar to that on the test set, this phenomenon proved that the model had good robustness. The model can not only judge the health condition of samples in training set but also diagnosis unknown samples. ROC curve was also used to evaluate the model's ability in diagnosing diseases, the ROC cu.....
Document: The model achieved a 94% ACC performance in the test set. From the training images, we could find that the performance of the model on the training set is similar to that on the test set, this phenomenon proved that the model had good robustness. The model can not only judge the health condition of samples in training set but also diagnosis unknown samples. ROC curve was also used to evaluate the model's ability in diagnosing diseases, the ROC curve of the model mentioned above is shown in Figure 8 .
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