| dc.contributor.author | García Peñalvo, Francisco J. | |
| dc.contributor.author | Vázquez Ingelmo, Andrea | |
| dc.contributor.author | García Holgado, Alicia | |
| dc.date.accessioned | 2023-12-05T19:13:43Z | |
| dc.date.available | 2023-12-05T19:13:43Z | |
| dc.date.issued | 2022 | |
| dc.identifier.citation | García-Peñalvo, F. J., Vázquez-Ingelmo, A., & García-Holgado, A. (2022). Fostering Decision-Making Processes in Health Ecosystems Through Visual Analytics and Machine Learning. In P. Zaphiris & A. Ioannou (Eds.), Learning and Collaboration Technologies: Designing the Learner and Teacher Experience. 9th International Conference, LCT 2022, Held as Part of the 24th HCI International Conference, HCII 2022. Virtual Event, June 26 – July 1, 2022. Proceedings, Part II (pp. 262–273). Springer Nature. https://doi.org/10.1007/978-3-031-05675-8_20 | es_ES |
| dc.identifier.issn | 0302-9743 | |
| dc.identifier.uri | http://hdl.handle.net/10366/153826 | |
| dc.description.abstract | Data-intensive contexts, such as health, use information systems to
merge, synthesize, represent, and visualize data by using interfaces to ease
decision-making processes. All data management processes play an essential role
in exploiting data’s strategic value from acquisition to visualization. Technological
ecosystems allow the deployment of highly complex services while supporting
their evolutionary nature. However, there is a challenge regarding the design of
high-level interfaces that adapt to the evolving nature of data. The AVisSA project
is focused on tackling the development of an automatic dashboard generation
system (meta-dashboard) using Domain Engineering and Artificial Intelligence
techniques. This approach makes it possible to obtain dashboards from data flows
in technological ecosystems adapted to specific domains. The implementation of
the meta-dashboard will make intensive use of user experience testing throughout
its development, which will allowthe involvement of other actors in the ecosystem
as stakeholders (public administration, health managers, etc.). These actors will
be able to use the data for decision-making and design improvements in health
provision. | es_ES |
| dc.format.mimetype | application/pdf | |
| dc.language.iso | eng | es_ES |
| dc.rights | Atribución-NoComercial-CompartirIgual 4.0 Internacional | * |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-sa/4.0/ | * |
| dc.subject | Domain engineering | es_ES |
| dc.subject | SPL | es_ES |
| dc.subject | Meta-modeling | es_ES |
| dc.subject | Information dashboards | es_ES |
| dc.subject | Information systems | es_ES |
| dc.subject | Healthcare | es_ES |
| dc.subject | Health domain | es_ES |
| dc.title | Fostering Decision-Making Processes in Health Ecosystems Through Visual Analytics and Machine Learning | es_ES |
| dc.type | info:eu-repo/semantics/article | es_ES |
| dc.subject.unesco | 3212 Salud Publica | es_ES |
| dc.subject.unesco | 1203.17 Informática | es_ES |
| dc.identifier.doi | 10.1007/978-3-031-05675-8_20 | |
| dc.relation.projectID | PID2020-118345RB-I00 | es_ES |
| dc.rights.accessRights | info:eu-repo/semantics/openAccess | es_ES |
| dc.identifier.essn | 1611-3349 | |
| dc.volume.number | 13329 | es_ES |
| dc.page.initial | 262 | es_ES |
| dc.page.final | 273 | es_ES |
| dc.type.hasVersion | info:eu-repo/semantics/acceptedVersion | es_ES |