Hypertension prediction model based on artificial neural network
In order to accurately predict patients with hypertension,the article proposes a hypertension prediction model based on artificial neural network,(artificial neural network,ANN).This model introduces a batch normalization layer(batch normalization,BN)into the original ANN model,and residual connection to improve the defects of the original ANN.Experiments show that the convergence speed of this model is significantly higher than that of the original model,and it can effectively speed up the training process of the model.The results can be used for the treatment of hypertension and provide reference for early prediction and intervention.
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