Díez Vegas, Francisco JavierLuque Gallego, ManuelArias Calleja, ManuelPérez Martín, Jorge2026-01-302026-01-302021-06-30Diez, 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.https://hdl.handle.net/20.500.14468/31649This 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.pdfThe 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.eninfo:eu-repo/semantics/openAccess32 Ciencias Médicas1203 Ciencia de los ordenadoresactas de congresoODS 3 - Salud y bienestarODS 9 - Industria, innovación e infraestructura