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dc.contributor.authorVázquez-Ingelmo, Andrea
dc.contributor.authorGarcía-Holgado, Alicia 
dc.contributor.authorGarcía-Peñalvo, Francisco J. 
dc.contributor.authorPérez-Sánchez, Pablo
dc.contributor.authorAntúnez-Muiños, Pablo
dc.contributor.authorSánchez-Puente, Antonio
dc.contributor.authorVicente-Palacios, Víctor
dc.contributor.authorDorado-Díaz, Pedro Ignacio
dc.contributor.authorSánchez, Pedro Luis
dc.date.accessioned2023-12-05T19:07:31Z
dc.date.available2023-12-05T19:07:31Z
dc.date.issued2023
dc.identifier.issn0302-9743
dc.identifier.urihttp://hdl.handle.net/10366/153824
dc.description.abstractThe prevalence of artificial intelligence (AI) in our daily lives is often exaggerated by the media, leading to a positive public perception while overlooking potential problems. In the field of medicine, it is crucial to educate future healthcare professionals on the advantages and disadvantages of AI and to emphasize the importance of creating fair, ethical, and reproducible models. The KoopaML platform was developed to provide an educational and user-friendly interface for inexperienced users to create AI pipelines. This study analyzes the quantitative and interaction data gathered from a usability test involving physicians from the University Hospital of Salamanca, with the aim of identifying new interaction paradigms to improve the platform’s usability. The results shown that the platform is difficult to learn for inexperienced users due to its contents related to AI. Following these results, a set of improvements are proposed for the next version of KoopaML, focusing on reducing the interactions needed to create the pipelines.es_ES
dc.format.mimetypeapplication/pdf
dc.language.isoenges_ES
dc.rightsAtribución-NoComercial-CompartirIgual 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/*
dc.subjectInformation systemes_ES
dc.subjectMedical data managementes_ES
dc.subjectArtificial Intelligencees_ES
dc.subjectHealth platformes_ES
dc.subjectHCIes_ES
dc.subjectUsabilityes_ES
dc.subjectSUSes_ES
dc.titleAre Textual Recommendations Enough? Guiding Physicians Toward the Design of Machine Learning Pipelines Through a Visual Platformes_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.subject.unesco1203.17 Informáticaes_ES
dc.subject.unesco1203.04 Inteligencia Artificiales_ES
dc.subject.unesco3212 Salud Publicaes_ES
dc.identifier.doi10.1007/978-3-031-42935-4_20
dc.relation.projectIDPID2020-118345RB-I00es_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
dc.identifier.essn1611-3349
dc.volume.number14113es_ES
dc.page.initial247es_ES
dc.page.final255es_ES
dc.type.hasVersioninfo:eu-repo/semantics/acceptedVersiones_ES


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Atribución-NoComercial-CompartirIgual 4.0 Internacional
Except where otherwise noted, this item's license is described as Atribución-NoComercial-CompartirIgual 4.0 Internacional