Persona: Pérez Martín, Jorge
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Pérez Martín
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Jorge
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Publicación Quality analysis of a breast thermal images database(Sage Journals, 2023-02-02) Pérez Martín, Jorge::virtual::28::600; Sánchez Cauce, Raquel; Pérez Martín, Jorge; Pérez Martín, Jorge; Pérez Martín, Jorge; https://orcid.org/0000-0002-1128-3988The study and early detection of breast cancer are key for its treatment. We carry out an exhaustive analysis of the most used database for mastology research with infrared images, analyzing the anomalies according to five quality dimensions: completeness, correctness, concordance, plausibility, and currency. We established control queries that looked for these anomalies and that can be used to ensure the quality of the database. Finally, we briefly review the more than 40 papers that use this database and that do not mention any of these anomalies. When analyzing the database, we found 365 anomalies related to personal and clinical data, and thermal images. The errors found in our research may lead to a modification of the results and conclusions made in the articles found in the literature, serve as a basis for improvements in the quality of the database, and help future researchers to work with it.Publicación La infraestructura de la calidad para apoyar la contratación pública sostenible(2024) Massó Aguado, Daniel; Arbeloa Losada, Marta; García López, Paloma; Pérez Martín, JorgePublicación El papel de los consumidores para alcanzar los ODS(2024) Massó Aguado, Daniel; Arbeloa Losada, Marta; García López, Paloma; Pérez Martín, JorgePublicación Markov influence diagrams: a graphical tool for cost-effectiveness analysis(Society for Medical Decision Making, 2017-01-11) Yebra, Mar; Bermejo, Iñigo; Palacios Alonso, Miguel Ángel; Arias Calleja, Manuel::virtual::3078::600; Luque Gallego, Manuel::virtual::3079::600; Pérez Martín, Jorge::virtual::3080::600; Díez Vegas, Francisco Javier::virtual::6771::600; Arias Calleja, Manuel; Luque Gallego, Manuel; Pérez Martín, Jorge; Díez Vegas, Francisco Javier; Arias Calleja, Manuel; Luque Gallego, Manuel; Pérez Martín, Jorge; Díez Vegas, Francisco Javier; Arias Calleja, Manuel; Luque Gallego, Manuel; Pérez Martín, Jorge; Díez Vegas, Francisco JavierMarkov influence diagrams (MIDs) are a new type of probabilistic graphical models that extend influence diagrams in the same way as Markov decision trees extend decision trees. They have been designed to build state-transition models, mainly in medicine, and perform cost-effectiveness analysis. Using a causal graph that may contain several variables per cycle, MIDs can model various features of the patient without multiplying the number of states; in particular, they can represent the history of the patient without using tunnel states. OpenMarkov, an open-source tool, allows the decision analyst to build and evaluate MIDs—including cost-effectiveness analysis and several types of deterministic and probabilistic sensitivity analysis—with a graphical user interface, without writing any code. This way, MIDs can be used to easily build and evaluate complex models whose implementation as spreadsheets or decision trees would be cumbersome or unfeasible in practice. Furthermore, many problems that previously required discrete event simulation can be solved with MIDs, i.e., within the paradigm of state-transition models, in which many health economists feel more comfortable.Publicación Cost-effectiveness analysis with new models of artificial intelligence. Medical applications(Universidad Nacional de Educación a Distancia (España). Escuela Internacional de Doctorado. Programa de Doctorado en Sistemas Inteligentes, 2019) Pérez Martín, Jorge; Díez Vegas, Francisco JavierPublicación Evaluation of Markov models with discontinuities(Society for Medical Decision Making, 2019-02-07) Bermejo, Iñigo; Pérez Martín, Jorge; Díez Vegas, Francisco JavierBackground. Several methods, such as the half-cycle correction and the life-table method, were developed to attenuate the error introduced in Markov models by the discretization of time. Elbasha and Chhatwal have proposed alternative “corrections” based on numerical integration techniques. They present an example whose results suggest that the trapezoidal rule, which is equivalent to the half-cycle correction, is not as accurate as Simpson’s 1/3 and 3/8 rules. However, they did not take into consideration the impact of discontinuities. Objective. To propose a method for evaluating Markov models with discontinuities. Design. Applying the trapezoidal rule, we derive a method that consists of adjusting the model by setting the cost at each point of discontinuity to the mean of the left and right limits of the cost function. We then take from the literature a model with a cycle length of 1 year and a discontinuity on the cost function and compare our method with other “corrections” using as the gold standard an equivalent model with a cycle length of 1 day. Results. As expected, for this model, the life-table method is more accurate than assuming that transitions occur at the beginning or the end of cycles. The application of numerical integration techniques without taking into account the discontinuity causes large errors. The model with averaged cost values yields very small errors, especially for the trapezoidal and the 1/3 Simpson rules. Conclusion. In the case of discontinuities, we recommend applying the trapezoidal rule on an averaged model because this method has a mathematical justification, and in our empirical evaluation, it was more accurate than the sophisticated 3/8 Simpson rule.Publicación Cost-effectiveness analysis with unordered decisions(Elsevier, 2021-07) Díez Vegas, Francisco Javier; Luque Gallego, Manuel; Arias Calleja, Manuel; Pérez Martín, JorgeIntroduction Cost-effectiveness analysis (CEA) is used increasingly in medicine to determine whether the health benefit of an intervention is worth the economic cost. Decision trees, the standard decision modeling technique for non-temporal domains, can only perform CEAs for very small problems. Influence diagrams can model much larger problems, but only when the decisions are totally ordered. Objective To develop a CEA method for problems with unordered or partially ordered decisions, such as finding the optimal sequence of tests for diagnosing a disease. Methods We explain how to model those problems using decision analysis networks (DANs), a new type of probabilistic graphical model, somewhat similar to Bayesian networks and influence diagrams. We present an algorithm for evaluating DANs with two criteria, cost and effectiveness, and perform some experiments to study its computational efficiency. We illustrate the representation framework and the algorithm using a hypothetical example involving two therapies and several tests and then present a DAN for a real-world problem, the mediastinal staging of non-small cell lung cancer. Results The evaluation of a DAN with two criteria, cost and effectiveness, returns a set of intervals for the willingness to pay, separated by incremental cost-effectiveness ratios (ICERs). The cost, the effectiveness, and the optimal intervention are specific for each interval, i.e., they depend on the willingness to pay. Conclusion Problems involving several unordered decisions can be modeled with DANs and evaluated in a reasonable amount of time. OpenMarkov, an open-source software tool developed by our research group, can be used to build the models and evaluate them using a graphical user interface.Publicación Teaching Probabilistic Graphical Models with OpenMarkov(MDPI, 2022-11-30) Díez Vegas, Francisco Javier; Arias Calleja, Manuel; Pérez Martín, Jorge; Luque Gallego, ManuelOpenMarkov is an open-source software tool for probabilistic graphical models. It has been developed especially for medicine, but has also been used to build applications in other fields and for tuition, in more than 30 countries. In this paper we explain how to use it as a pedagogical tool to teach the main concepts of Bayesian networks and influence diagrams, such as conditional dependence and independence, d-separation, Markov blankets, explaining away, optimal policies, expected utilities, etc., and some inference algorithms: logic sampling, likelihood weighting, and arc reversal. The facilities for learning Bayesian networks interactively can be used to illustrate step by step the performance of the two basic algorithms: search-and-score and PC.Publicación Cost-effectiveness of Pediatric Bilateral Cochlear Implantation in Spain(Wiley Online Library, 2017) Artaso, Miguel A.; Díez, Francisco Javier; Pérez Martín, JorgeObjective: To determine the incremental cost-effectiveness of bilateral versus unilateral cochlear implantation for one-year-old children suffering from bilateral sensorineural severe to profound hearing loss from the perspective of the Spanish public health system. Study Design: Cost-utility analysis. Methods: We conducted a general-population survey to estimate the quality of life increase contributed by the second implant. We built a Markov influence diagram and evaluated it for a life-long time horizon with a 3% discount rate in the base case. Results: The incremental cost-effectiveness ratio (ICER) of simultaneous bilateral implantation with respect to unilateral implantation for one-year-old children with severe to profound deafness is €10,323 per quality-adjusted life year (QALY). For sequential bilateral implantation, it rises to €11,733/QALY. Both options are cost-effective for the Spanish health system, whose willingness to pay is estimated at around €30,000/QALY. The probabilistic sensitivity analysis shows that the probability of bilateral implantation being cost-effective reaches 100% for that cost-effectiveness threshold. Conclusions: Bilateral implantation is clearly cost-effective for the population considered. If possible, it should be done simultaneously, i.e., in one surgical operation, because it is as safe and effective as sequential implantation, and saves costs for the system and for users and their families. Sequential implantation is also cost-effective for children who have received the first implant recently, but it is difficult to determine when it ceases to be so because of the lack of detailed data. These results are specific for Spain but the model can easily be adapted to other countries. Level of Evidence: 2CPublicación Análisis de coste-efectividad en OpenMarkov. Aplicación al implante coclear bilateral pediátrico en España(Universidad Nacional de Educación a Distancia (España). Escuela Técnica Superior de Ingeniería Informática. Departamento de Inteligencia Artificial., 2015-10-05) Pérez Martín, Jorge; Díez Vegas, Francisco JavierEl uso de implantes cocleares es, a día de hoy la terapia más efectiva para el tratamiento de la sordera severa y profunda. Diferentes estudios han demostrado que el implante coclear unilateral es coste-efectivo en niños y en adultos. Investigaciones recientes indican que el implante coclear bilateral (un implante en cada oído) es coste-efectivo en niños, pero el grado de incertidumbre sigue siendo elevado. El objetivo de este estudio consiste en determinar con la mayor precisión posible si el implante coclear bilateral pediátrico es coste-efectivo. Con este fin se ha construido un modelo gráfico probabilista que representa los sucesos que pueden producirse a lo largo de la vida del usuario, su impacto en la calidad de vida y los costes asociados, distinguiendo los costes que cubre el sistema nacional de sanidad de los que en España asumen los usuarios y sus familias. La construcción y la evaluación del modelo se han realizado con la herramienta de software libre OpenMarkov, desarrollada en Centro de Investigación sobre Sistemas Inteligentes de Ayuda a la Decisión (CISIAD) de la UNED, para lo cual se han añadido nuevas funcionalidades y se han extendido algunas de las ya existentes. Varios estudios han estimado que la disposición a pagar (también conocida como “umbral de coste-efectividad”) implícitamente utilizada por el sistema de sanidad español si sitúa entre entre 30.000 y 35.000 € por año de vida ajustado en calidad (AVAC). Según los resultados de nuestro modelo, la razón de coste-efectividad incremental (RCEI) del implante simultáneo frente al unilateral para niños de un año de edad es de 12.133 €/AVAC, lo cual implica que conviene poner dos implantes todos los que los necesitan. El análisis de sensibilidad confirma esta conclusión, pues para un umbral de 30.000 €/AVAC la probabilidad de que esta intervención sea coste-efectivo alcanza el 98 %. Incluso en el caso de que el sistema nacional de salud asumiera los costes que en nuestro país cubren actualmente las familias,la intervención seguiría siendo coste-efectiva, con una RCEI de 17.263 €/AVAC y una probabilidad del 94 %. La implantación debe hacerse de forma simultánea, es decir, en una sola operación quirúrgica, porque la implantación secuencial tiene la misma efectividad pero mayor coste para el sistema sanitario y para la familia. Nuestro modelo no es capaz de estimar la RCEI para niños mayores de un año porque la efectividad depende de muchos factores, principalmente de la edad actual, cuándo apareció la sordera, cuándo fue diagnosticada y, en su caso, cuándo se realizó el primer implante. Este modelo estará disponible públicamente para que otros investigadores puedan reproducir los resultados y adaptarlo a otros contextos. En particular, sería interesante analizar la RCEI en adultos y en otros países.