Advanced Algorithms for Medical Decision Analysis. Implementation in OpenMarkov
| Autor: | Francisco Javier Díez, Jorge Pérez-Martín, Inigo Bermejo, Manuel Arias, Miguel Ángel Artaso, Manuel Luque |
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| Rok vydání: | 2017 |
| Předmět: |
Medical algorithm
020205 medical informatics Computer science Management science business.industry media_common.quotation_subject Decision tree Bayesian network 02 engineering and technology Scarcity 03 medical and health sciences 0302 clinical medicine Software 0202 electrical engineering electronic engineering information engineering Spite Influence diagram 030212 general & internal medicine business Algorithm media_common Decision analysis |
| Zdroj: | Artificial Intelligence in Medicine ISBN: 9783319597577 AIME |
| DOI: | 10.1007/978-3-319-59758-4_43 |
| Popis: | In spite the important advantages of influence diagrams over decision trees, including the possibility of solving much more complex problems, the medical literature still contains around 10 decision trees for each influence diagram. In this paper we analyse the reasons for the low acceptance of influence diagrams in health decision analysis, in contrast with its success in artificial intelligence. One of the reasons is the difficulty of representing asymmetric problems. Another one was the lack of algorithms for explaining the reasoning and performing cost-effectiveness analysis, as well as the scarcity of user-friendly software tools for sensitivity analysis. In this paper we review the research conducted by our group in the last 25 years, crystallised in the open-source software tool OpenMarkov, explaining how it has tried to address those challenges. |
| Databáze: | OpenAIRE |
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