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Título
Fostering Decision-Making Processes in Health Ecosystems Through Visual Analytics and Machine Learning
Autor(es)
Assunto
Domain engineering
SPL
Meta-modeling
Information dashboards
Information systems
Healthcare
Health domain
Clasificación UNESCO
3212 Salud Publica
1203.17 Informática
Fecha de publicación
2022
Citación
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
Resumen
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.
URI
ISSN
0302-9743
DOI
10.1007/978-3-031-05675-8_20
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- GRIAL. Artículos [441]