From predictions to prescriptions: A data-driven response to COVID-19
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DOI: 10.1007/s10729-020-09542-0
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- Fattahi, Mohammad & Keyvanshokooh, Esmaeil & Kannan, Devika & Govindan, Kannan, 2023. "Resource planning strategies for healthcare systems during a pandemic," European Journal of Operational Research, Elsevier, vol. 304(1), pages 192-206.
- Soltanisehat, Leili & González, Andrés D. & Barker, Kash, 2023. "Modeling social, economic, and health perspectives for optimal pandemic policy decision-making," Socio-Economic Planning Sciences, Elsevier, vol. 86(C).
- Víctor Blanco & Ricardo Gázquez & Marina Leal, 2023. "Mathematical optimization models for reallocating and sharing health equipment in pandemic situations," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 31(2), pages 355-390, July.
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Keywords
COVID-19; Epidemiological modeling; Machine learning; Optimization;All these keywords.
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