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Fecha
2021-06-30
Derechos de acceso
info:eu-repo/semantics/openAccess
Título de la revista
ISSN de la revista
Título del volumen
Editorial
Bayesian Network Modelling Association
Citas
Resumen
The two formalisms most widely used for the representation and analysis of decision problems in medicine are decision trees and Markov flat models, which seriously limit the complexity of the problems that can be addressed. In contrast, probabilistic graphical models (PGMs) can represent the state and the evolution of the system (the patient) using much richer structures, but they are rarely used for economic evaluations in medicine given that, until recently, they could not perform cost-effectiveness analysis (CEA). In this paper we summarize the research done by our group, developing new types of PGMs and new algorithms for CEA and implementing them in OpenMarkov, an open-source tool especially designed for medicine.
Descripción
This is the author accepted manuscript. Accepted for publication on 30 June 2021 in Proceedings of the Fifteenth UAI Bayesian Modelling Applications Workshop (BMAW’21). The final published version is available at https://bnma.co/uai2021-apps-workshop/papers/BMAW-2021_paper_19.pdf
Categorías UNESCO
Palabras clave
Citación
Diez, F. J., Luque, M., Arias, M., & Pérez-Martín, J. (2021, junio 30). Cost-effectiveness analysis with probabilistic graphical models. 15th Bayesian Modeling Applications Workshop (BMAW-2021), Clayton, Australia.
Centro
Facultad de Ciencias
Departamento
Estadística, Investigación Operativa y Cálculo Numérico