Search Results (All Fields:"sensitivity analysis") - e-spacio
http://e-spacio.uned.es/fez/
Universidad Nacional de Educación a DistanciaspFez 2.1 RC3http://blogs.law.harvard.edu/tech/rssAnalysis of ultrasound images and clinical data in two clinical scenarios: prediction of failure of induction of labor and risk of preterm delivery
http://e-spacio.uned.es/fez/view/bibliuned:master-ETSInformatica-IAA-Migarcia
This work explores the use of radiomics and machine learning to extract relevant biomarkers from ultrasound (US) images that can be used in obstetric practice. Two clinical applications are studied: the prediction of induction of labor (IOL) failure based on clinical data and US images obtained prior to IOL, and the estimation of risk of preterm birth based on routinely US images acquired in the 20th week of pregnancy. Several machine learning classifiers and feature selection techniques are tested and the results are compared. The best model for the prediction of IOL failure was a random forest that model obtained an AUC of 0.75, with 69% sensitivity and 71% specificity. The best model for the prediction of preterm birth was a random forest that obtained an AUC of 0.77 AUC, with 71% sensitivity and 69% specificity . These preliminary results suggest that features obtained from US images can be used to estimate risks in these two obstetric problems. Transvaginal US is cheap, widely available at hospitals, and performed routinely. Therefore these method can be easily implemented in clinical practice and help practitioners choose a most personalized treatment for each patient, improving the outcomes. Further validation with a largest and more diverse dataset is needed, especially to assess how the image analysis methods work with images from different US vendors.2020-10-14T22:40:36Z
García Ocaña, María Inmaculada
Markov influence diagrams: a graphical tool for cost-effectiveness analysis
http://e-spacio.uned.es/fez/view/bibliuned:95-Jperez-002
Markov 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.2020-06-17T22:57:50Z
Díez, Francisco J.
og Yebra, Mar
og Bermejo, Iñigo
og Palacios-Alonso, Miguel Angel
og Arias Calleja, Manuel
og Luque, Manuel
og Pérez-Martín, Jorge
New types of probabilistic graphical models: applications to medicine
http://e-spacio.uned.es/fez/view/tesisuned:IngInf-Ibermejo
Probabilistic graphical models (PGMs) play a major role in much of the modern research in reasoning with uncertainty, decision analysis, planning, pattern recognition, and many other areas. Several types of PGMs have been proposed in the last two decades. However, there are some problems for which none of these types are appropriate. For example, none of the types of PGMs proposed has been widely adopted for representing and solving asymmetric decision problems. Decision analysis networks (DANs) have been recently proposed by our research group and they needed efficient evaluation algorithms in order to be applicable to real-world problems. In this thesis, I propose a new algorithm that evaluates DANs by recursively decomposing them into a set of symmetric DANs, which can then be evaluated with standard algorithms, such as variable elimination or arc reversal. The efficiency of this algorithm matches that of the algorithms proposed for other asymmetric representations. Similarly, existing types of PGMs were not apt as dynamic modeling methods for cost-effectiveness analysis (CEA). The existing dynamic PGMs are burdened by the complexity of their evaluation and can only solve unicriterion problems. Only Markov infuence diagrams (MIDs), a more restricted type of dynamic PGMs also proposed by our research group, are suitable to build complex dynamic models to perform CEA. I have developed new types of potentials and new sensitivity analysis algorithms, with which I have been able to replicate as MIDs several models proposed in the literature and to build two new models for CEA: one for malignant pleural effusion and another one for mammography screening. Finally, with the help of an expert, we have built a decision-support system for cochlear implant programming (i.e., parameter tuning) based on PGMs. In this thesis, we also describe tuning networks, a new type of PGM we developed because existing PGMs were not suitable to model the behavior of systems with a high number of tunable parameters. This decision-support system is now routinely used at a hearing clinic in Antwerp (Belgium) to assist audiologists in the programming of cochlear implants. All the contributions to PGMs described in this thesis have been implemented in OpenMarkov, an open-source software tool developed at the UNED, and are publicly available.2016-10-21T19:27:27Z
Bermejo Delgado, Iñigo
Cost-effectiveness of Pediatric Bilateral Cochlear Implantation in Spain
http://e-spacio.uned.es/fez/view/bibliuned:95-Jperez-001
Objective: 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: 2C2020-06-11T22:26:51Z
Pérez-Martín, Jorge
og Artaso, Miguel A.
og Díez, Francisco J.