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_9
Snippet: LSTM is the core of attention deep learning algorithm. It can learn the features of the data far apart in the text data, which provides support for learning the relationship between physiological parameters mentioned above, and improves the performance of the auxiliary diagnostic model. The purpose of LSTM is to study the joint representation of different physiological parameters. In clinical practice, diseaserelated physiological parameters are .....
Document: LSTM is the core of attention deep learning algorithm. It can learn the features of the data far apart in the text data, which provides support for learning the relationship between physiological parameters mentioned above, and improves the performance of the auxiliary diagnostic model. The purpose of LSTM is to study the joint representation of different physiological parameters. In clinical practice, diseaserelated physiological parameters are not independent, so LSTM is more suitable for analyzing textual medical data with joint characteristics than traditional methods. The schematic diagram of LSTM layer is shown in Figure 3 .
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