Publicación: Optimización de árboles de estrategia unicriterio y de coste-efectividad
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2020-10-02
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info:eu-repo/semantics/openAccess
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Universidad Nacional de Educación a Distancia (España). Escuela Técnica Superior de Ingeniería Informática. Departamento de Inteligencia Artificial
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Introduction: A cost-effectiveness analysis (CEA) helps us select the most effective intervention for the financial budget we have. In these analyzes through CEP, we generated several lambda intervals, each with the optimal intervention, its cost and expected effectiveness. Being able to represent these lambda intervals, through a graphic model, will help us see all the available information and will speed us up to make a decision. If we can optimize this tree, it will be easier to study and understand it. Objective: To find the algorithm that returns the best optimization of the generated tree after applying the deterministic CEA analysis. Methods: Applying pruning techniques on the tree nodes (variable exchange, elimination of redundancies, lambda displacement) in a search algorithm, we will be able to get partial results of the search optimization, until we reach the most optimal tree optimization result created with CEP results. Results: Once optimized with the most appropriate pruning techniques and algorithms, we will have a graphic model where the different options can be observed in a more effective and clear way than when we use a textual description. Conclusion: Through the open source software tool "OpenMarkov" the possibility of graphically displaying the result of a deterministic CEA analysis has been implemented. With this new tool we can graphically evaluate the results that were previously shown in a table, and that did not allow us to appreciate in the same detail, each of the concepts that are observed in each branch of the tree.
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Facultades y escuelas::E.T.S. de Ingeniería Informática
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Inteligencia Artificial