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dc.contributor.author | González Arteaga, María Teresa | |
dc.contributor.author | Andrés Calle, Rocío de | |
dc.contributor.author | Peral, Marta | |
dc.date.accessioned | 2020-02-27T13:09:20Z | |
dc.date.available | 2020-02-27T13:09:20Z | |
dc.date.issued | 2017 | |
dc.identifier.citation | Progress in Artifitial Intelligence, 2017, vol. 6, p. 235–244. | es |
dc.identifier.issn | 2192-6352 | es |
dc.identifier.uri | http://uvadoc.uva.es/handle/10324/40549 | |
dc.description.abstract | This work introduces a non-traditional perspective about the problem of measuring the stability of agents’ preferences. Specifically, the cohesiveness of preferences at different moments of time is explored under the assumption of considering dichotomous evaluations. The general concept of time cohesiveness measure is introduced as well as a particular formulation based on the consideration of any two successive moments of time, the sequential time cohesiveness measure. Moreover, some properties of the novel measure are also provided. Finally, and in order to emphasize the adaptability of our proposal to real situations, a factual case of study about clinical decision-making is presented. Concretely, the study of preference stability for life-sustaining treatments of patients with advanced cancer at end of life is analysed. The research considers patients who express their opinions on three life-sustaining treatments at four consecutive periods of time. The novel measure provides information of patients preference stability along time and considers the possibility of cancer metastases | es |
dc.format.mimetype | application/pdf | es |
dc.language.iso | eng | es |
dc.publisher | Springer | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.subject.classification | Time cohesiveness measure. Dichotomous opinions. Preference stability. Patients’ preferences | es |
dc.title | Preference stability along time: the time cohesiveness measure | es |
dc.type | info:eu-repo/semantics/article | es |
dc.rights.holder | Springer | es |
dc.identifier.doi | 10.1007/s13748-017-0119-3 | es |
dc.relation.publisherversion | https://doi.org/10.1007/s13748-017-0119-3 | es |
dc.identifier.publicationfirstpage | 235 | es |
dc.identifier.publicationissue | 3 | es |
dc.identifier.publicationlastpage | 244 | es |
dc.identifier.publicationtitle | Progress in Artificial Intelligence | es |
dc.identifier.publicationvolume | 6 | es |
dc.peerreviewed | SI | es |
dc.description.project | Este trabajo forma parte del proyecto de investigación con financiación nacional: MEC-FEDER Grant ECO2016-77900-P | es |
dc.identifier.essn | 2192-6360 | es |
dc.type.hasVersion | info:eu-repo/semantics/draft | es |