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Cost-effectiveness analysis with probabilistic graphical models

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dc.contributor.authorDíez Vegas, Francisco Javier
dc.contributor.authorLuque Gallego, Manuel
dc.contributor.authorArias Calleja, Manuel
dc.contributor.authorPérez Martín, Jorge
dc.coverage.spatialClayton, Australia
dc.coverage.temporal2021-07-30
dc.date.accessioned2026-01-30T09:49:50Z
dc.date.available2026-01-30T09:49:50Z
dc.date.issued2021-06-30
dc.descriptionThis 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
dc.description.abstractThe 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.en
dc.description.provenanceSubmitted by Óscar Soto López (osoto@pas.uned.es) on 2026-01-30T09:49:34Z workflow start=Step: editstep - action:claimaction No. of bitstreams: 1 diez2021bmaw-for-public-repository_MANUEL LUQUE GALLEGO.pdf: 301531 bytes, checksum: 596eaa603bface3d380cef0e8a3f3232 (MD5)en
dc.description.provenanceStep: editstep - action:editaction Approved for entry into archive by Óscar Soto López(osoto@pas.uned.es) on 2026-01-30T09:49:50Z (GMT)en
dc.description.provenanceMade available in DSpace on 2026-01-30T09:49:50Z (GMT). No. of bitstreams: 1 diez2021bmaw-for-public-repository_MANUEL LUQUE GALLEGO.pdf: 301531 bytes, checksum: 596eaa603bface3d380cef0e8a3f3232 (MD5) Previous issue date: 2021-06-30en
dc.description.versionversión final
dc.identifier.citationDiez, 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.
dc.identifier.urihttps://hdl.handle.net/20.500.14468/31649
dc.language.isoen
dc.publisherBayesian Network Modelling Association
dc.relation.centerFacultad de Ciencias
dc.relation.congressFifteenth UAI Bayesian Modelling Applications Workshop (BMAW’21)
dc.relation.departmentEstadística, Investigación Operativa y Cálculo Numérico
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.es
dc.subject32 Ciencias Médicas
dc.subject1203 Ciencia de los ordenadores
dc.subject.odsODS 3 - Salud y bienestar
dc.subject.odsODS 9 - Industria, innovación e infraestructura
dc.titleCost-effectiveness analysis with probabilistic graphical modelsen
dc.typeactas de congresoes
dc.typeconference proceedingsen
dspace.entity.typePublication
relation.isAuthorOfPublicationc6032e20-a1d0-49b9-92e3-5c9f624ab143
relation.isAuthorOfPublicatione94799f0-bdd0-45be-b6b2-426269f6ee46
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relation.isAuthorOfPublication.latestForDiscoveryc6032e20-a1d0-49b9-92e3-5c9f624ab143
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