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dc.contributor.authorMartínez-Salvador, Begoña
dc.contributor.authorMarcos, Mar
dc.contributor.authorPalau, Patricia
dc.contributor.authorDomínguez Mafé, Eloy
dc.date.accessioned2023-02-28T08:23:05Z
dc.date.available2023-02-28T08:23:05Z
dc.date.issued2023
dc.identifier.citationMARTÍNEZ-SALVADOR, Begoña, et al. A model-driven transformation approach for the modelling of processes in clinical practice guidelines. Artificial Intelligence in Medicine, 2023, vol. 137, p. 102495.ca_CA
dc.identifier.urihttp://hdl.handle.net/10234/201873
dc.description.abstractClinical Practice Guidelines (CPGs) include recommendations aimed at optimising patient care, informed by a review of the available clinical evidence. To achieve their potential benefits, CPG should be readily available at the point of care. This can be done by translating CPG recommendations into one of the languages for Computer-Interpretable Guidelines (CIGs). This is a difficult task for which the collaboration of clinical and technical staff is crucial. However, in general CIG languages are not accessible to non-technical staff. We propose to support the modelling of CPG processes (and hence the authoring of CIGs) based on a transformation, from a preliminary specification in a more accessible language into an implementation in a CIG language. In this paper, we approach this transformation following the Model-Driven Development (MDD) paradigm, in which models and transformations are key elements for software development. To demonstrate the approach, we implemented and tested an algorithm for the transformation from the BPMN language for business processes to the PROforma CIG language. This implementation uses transformations defined in the ATLAS Transformation Language. Additionally, we conducted a small experiment to assess the hypothesis that a language such as BPMN can facilitate the modelling of CPG processes by clinical and technical staff.ca_CA
dc.description.sponsorShipFunding for open access charge: CRUE-Universitat Jaume I
dc.format.extent15 p.ca_CA
dc.format.mimetypeapplication/pdfca_CA
dc.language.isoengca_CA
dc.publisherElsevierca_CA
dc.relation.isPartOfArtificial Intelligence in Medicine, Volume 137, March 2023.ca_CA
dc.rights0933-3657/© 2023 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/bync-nd/4.0/).ca_CA
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/ca_CA
dc.subjectClinical practice guidelinesca_CA
dc.subjectComputer-interpretable guidelinesca_CA
dc.subjectModelling of processes in clinical practice guidelinesca_CA
dc.subjectModel-driven developmentca_CA
dc.subjectBPMNca_CA
dc.subjectPROformaca_CA
dc.subjectATLAS transformation languageca_CA
dc.titleA model-driven transformation approach for the modelling of processes in clinical practice guidelinesca_CA
dc.typeinfo:eu-repo/semantics/articleca_CA
dc.identifier.doihttps://doi.org/10.1016/j.artmed.2023.102495
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessca_CA
dc.relation.publisherVersionhttps://www.sciencedirect.com/science/article/pii/S093336572300009Xca_CA
dc.type.versioninfo:eu-repo/semantics/publishedVersionca_CA
project.funder.nameMinisterio de Economía y Competitividadca_CA
oaire.awardNumberTIN2014-53749-C2-1-R.ca_CA
dc.subject.ods3. Salud y bienestar


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0933-3657/© 2023 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/bync-nd/4.0/).
Excepto si se señala otra cosa, la licencia del ítem se describe como: 0933-3657/© 2023 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/bync-nd/4.0/).