Development and evaluation of a deep learning approach for modeling seasonality and trends in hand-f...
Development and evaluation of a deep learning approach for modeling seasonality and trends in hand-foot-mouth disease incidence in mainland China
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London: Nature Publishing Group UK
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English
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London: Nature Publishing Group UK
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The high incidence, seasonal pattern and frequent outbreaks of hand, foot, and mouth disease (HFMD) represent a threat for millions of children in mainland China. And advanced response is being used to address this. Here, we aimed to model time series with a long short-term memory (LSTM) based on the HFMD notified data from June 2008 to June 2018 a...
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Development and evaluation of a deep learning approach for modeling seasonality and trends in hand-foot-mouth disease incidence in mainland China
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TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_6541597
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_6541597
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ISSN
2045-2322
E-ISSN
2045-2322
DOI
10.1038/s41598-019-44469-9
