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		<title>Hybrid Forecasting Model Sharpens Predictions of Seasonal Influenza Waves in China</title>
		<link>https://bioengineer.org/hybrid-forecasting-model-sharpens-predictions-of-seasonal-influenza-waves-in-china/</link>
		
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		<pubDate>Wed, 07 Oct 2026 03:03:24 +0000</pubDate>
				<category><![CDATA[Health]]></category>
		<category><![CDATA[BMC Infectious Diseases]]></category>
		<category><![CDATA[China]]></category>
		<category><![CDATA[Epidemiology]]></category>
		<category><![CDATA[hospital surveillance]]></category>
		<category><![CDATA[influenza A]]></category>
		<category><![CDATA[influenza B]]></category>
		<category><![CDATA[LSTM neural network]]></category>
		<category><![CDATA[Machine Learning]]></category>
		<category><![CDATA[Public Health]]></category>
		<category><![CDATA[SARIMA-LSTM hybrid model]]></category>
		<category><![CDATA[seasonality]]></category>
		<category><![CDATA[time-series forecasting]]></category>
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					<description><![CDATA[A six-year hospital surveillance study in Jiande, China, shows that a hybrid SARIMA-LSTM model improves forecasts of laboratory-confirmed influenza A and B cases, which peak in winter and spring.]]></description>
		
		
		
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