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《Intelligent Computer and Applications》 2019-04
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Deep LSTM-based hyperthyroidism forecast and application

YANG Yihao;WANG Mei;ZUO Ming;School of Computer Science and Technology,Donghua University;Ruijin Hospital,Shanghai Jiao Tong University School of Medicine;  
According to the stage characteristics of the development of hyperthyroidism,the LSTMdeep learning model is established. By using the learned model,the patient's key blood test indicators are input to predict the future value of the patient,so as to obtain the prediction of disease development in the later stage. In addition,the forecasting application prototype system is built based on Vue. js framework,which implements a series of functions such as index data input,model call and prediction result display. The research provides effective help for doctors' current diagnosis development and treatment plan evaluation.
【Fund】: 上海市科技创新行动计划(16JC1400803);; 上海市信息化发展专项(201801027)
【CateGory Index】: TP181;R581.1
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