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Data-driven forecasting of Flu, RSV, and COVID-19 related outcomes in the United States and Canada via Hankel dynamic mode decomposition.
Redman WT, Mullany LC
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Data-driven forecasting of Flu, RSV, and COVID-19 related outcomes in the United States and Canada via Hankel dynamic mode decomposition.

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Medicine & Health Published 2026 Verification Pending

Overview & Synopsis

Open access biomedical research article published in PLoS One.

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Indexed from repository: PubMed Central (pmc.ncbi.nlm.nih.gov)
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Document Information

Document Title Data-driven forecasting of Flu, RSV, and COVID-19 related outcomes in the United States and Canada via Hankel dynamic mode decomposition.
Author / Organization Redman WT, Mullany LC
Subject & Discipline PLoS One
Categories Medicine & Health
Publication Year 2026
License / Rights Open Access / Creative Commons
Resource Verification Listed PDF (Verification Pending)
Original Host Website PubMed Central (pmc.ncbi.nlm.nih.gov)
File Format application/pdf (Portable Document Format)
Language EN
Catalog ID DOC-38306
Original Source Link Visit Source Page on pmc.ncbi.nlm.nih.gov »