Hospital Readmission and Length-of-Stay Prediction Using an Optimized Hybrid Deep Model
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- Voyant, Cyril & Notton, Gilles & Kalogirou, Soteris & Nivet, Marie-Laure & Paoli, Christophe & Motte, Fabrice & Fouilloy, Alexis, 2017. "Machine learning methods for solar radiation forecasting: A review," Renewable Energy, Elsevier, vol. 105(C), pages 569-582.
- Peng, Yaohao & Nagata, Mateus Hiro, 2020. "An empirical overview of nonlinearity and overfitting in machine learning using COVID-19 data," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
- Manel Mata-Cases & Marc Casajuana & Josep Franch-Nadal & Aina Casellas & Conxa Castell & Irene Vinagre & Dídac Mauricio & Bonaventura Bolíbar, 2016. "Direct medical costs attributable to type 2 diabetes mellitus: a population-based study in Catalonia, Spain," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 17(8), pages 1001-1010, November.
- Pellerin, Robert & Perrier, Nathalie & Berthaut, François, 2020. "A survey of hybrid metaheuristics for the resource-constrained project scheduling problem," European Journal of Operational Research, Elsevier, vol. 280(2), pages 395-416.
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Keywords
readmission; length of stay; convolutional neural networks; genetic algorithm; diabetes; COVID-19;All these keywords.
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