Selected article for: "attention deep learning and automatically diagnose"
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_36
    Snippet: According to the confusion matrix, the specificity and sensitivity of the model can be obtained. The model achieved 92% specificity and 96% sensitivity in the test set. In conclusion, it can be proved that our attention deep learning model achieved a better performance, it can diagnose hyperlipidemia automatically and accurately, even faced with samples that do not exist in the training set......
    Document: According to the confusion matrix, the specificity and sensitivity of the model can be obtained. The model achieved 92% specificity and 96% sensitivity in the test set. In conclusion, it can be proved that our attention deep learning model achieved a better performance, it can diagnose hyperlipidemia automatically and accurately, even faced with samples that do not exist in the training set.

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