Early Warning of Infectious Diseases in Hospitals Based on Multi-Self-Regression Deep Neural Network

Table 1

Comparison of trend prediction results of infectious disease.

Comparison of trend prediction MAE results of infectious disease
	Influenza	HFMD	Viral hepatitis	Tuberculosis	Syphilis	Scarlet fever	Infectious diarrhea
MSRD	1.6252	0.5650	7.6897	1.2754	0.4974	0.2198	0.9564
Bi-LSTM	1.8185	0.6018	8.6141	1.4270	0.5565	0.2459	1.0701
DNN	1.9585	0.6403	9.2669	1.5369	0.5894	0.2734	1.1525
LSTM	1.8859	0.6402	8.9231	1.4999	0.5771	0.2550	1.1098
GRU	1.8731	0.6075	8.8633	1.4698	0.5732	0.2533	1.1022
SVM	1.7034	0.8923	8.1596	1.3367	0.5213	0.2303	1.0024
Lasso	1.9342	0.8864	9.1515	1.5178	0.5920	0.2615	1.1382
Bayes	2.0652	0.6759	9.7713	1.6206	0.6320	0.2792	1.2152
Comparison of trend prediction RMSE results of infectious disease
	Influenza	HFMD	Viral hepatitis	Tuberculosis	Syphilis	Scarlet fever	Infectious diarrhea
MSRD	3.8607	0.6069	9.1090	1.5705	1.7066	0.4459	1.253
Bi-LSTM	3.8588	0.8079	9.1744	1.5897	1.7177	0.4556	1.2663
DNN	3.8899	0.9209	9.3685	1.5924	1.7315	0.4492	1.2665
LSTM	3.8958	0.9170	9.2826	1.6048	1.7241	0.4499	1.2684
GRU	3.8763	0.8043	9.2361	1.5868	1.7155	0.4677	1.2620
SVM	3.8667	1.0531	9.4132	1.5829	1.8112	0.4565	1.2589
Lasso	4.5932	1.0859	10.9443	1.8903	2.0327	0.5305	1.4954
Bayes	3.9344	0.8462	9.3746	1.6106	1.7412	0.4544	1.2809