Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/89462
Título: | Decision models on therapies for intensive medicine |
Autor(es): | Passos, Maria Duarte, Júlio Miguel Marques Silva, Alvaro Manuel, Maria Quintas, Cesar |
Palavras-chave: | Decision Support Systems Intensive Care Units Intensive Medicine Optimization Techniques Therapies |
Data: | 2022 |
Editora: | Elsevier 1 |
Revista: | Procedia Computer Science |
Citação: | Passos, M., Duarte, J., Silva, Á., Manuel, M., & Quintas, C. (2022). Decision models on therapies for intensive medicine. Procedia Computer Science. Elsevier BV. http://doi.org/10.1016/j.procs.2022.10.142 |
Resumo(s): | Decision support models are crucial in intensive care units as they allow intensivists to make faster and better decisions. The application of optimization models in these areas becomes challenging given its complexity and multidisciplinary nature. The main objective of this study is to use the stochastic Hill Climbing optimization model in order to identify the best medication to treat the Covid Pneumonia problem, considering the top 3 medications administered as well as the cost of treatment. It should be noted that the problem to be analyzed in the optimization model was selected considering that the extracted data is from the time when Covid-19 was ravaging the intensive care units, so it will be the most interesting. The results obtained in this study denote that the n_iterations parameter was crucial in obtaining the optimal solution since all scenarios with this parameter set to a value of 1000 were able to return the optimal solution, unlike the other ones. |
Tipo: | Artigo em ata de conferência |
URI: | https://hdl.handle.net/1822/89462 |
DOI: | 10.1016/j.procs.2022.10.142 |
ISSN: | 1877-0509 |
Versão da editora: | https://www.sciencedirect.com/science/article/pii/S187705092201599X |
Arbitragem científica: | yes |
Acesso: | Acesso aberto |
Aparece nas coleções: |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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hodii22_passos.pdf | 489,12 kB | Adobe PDF | Ver/Abrir |
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