Collective intelligence and databases in eHealth: A survey1

Camacho, Azahara; Merayo, Mercedes G.; Núñez, Manuel

doi:10.3233/jifs-169144

Cited by 8 publications

(3 citation statements)

References 50 publications

(51 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It is also possible to identify areas of research regarding the significance of diversity in team members. The above, since it could be argued that in the absence of strong affiliation ties among team members, their level of diversity is greater [3];…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Impact of structure on team performance

González

Lopez²,

Arévalo³

2021

ing. Solidar

View full text Add to dashboard Cite

Introduction: This article is product of research on business self-organization developed at the Universidad Distrital Francisco Jose de Caldas on 2019-2020 starting from that collective intelligence (CI) has been viewed as an approach that enables from the use of the interactions among the agents and between these and the environment to increase the intelligence of the system; understood as the ability to take full advantage of distributed resources and to adapt nimbly to the changing conditions of the environment Methodology: in the first part, the conditions that may facilitate CI are explored through a review of the literature. In the second part an experiment is designed in a micro-world environment in which incorporate some of the conditions identified to facilitate the CI in the structure of a team and its performance is compared with a team that has a hierarchical structure. Results: the teams that have a structure with facilitates CI, present on average greater performance, coordination effectiveness and adaptability, as well as better interaction dynamics among the members. These teams present higher levels of interaction, information flows and activity among the participants, reflected in the number of interventions and in the use of the resources offered in the game. Conclusions: the increase in complexity that the application of IC inducers gives the team could be a predictor of better performances in environments of increasing complexity; in contrast to teams that have structures that reduce their complexity as the hierarchical structure. Originality: This article provides evidence regarding the incidence of roles in the performance of the company. Limitations: one of the main constraints is the virtual interaction between the participants and between them with the research team. Face-to-face interaction would allow more intensive use of affiliate links between participants. Keywords: collective intelligence, micro-world, hierarchical structure, organizational structure

show abstract

Section: Discussionmentioning

confidence: 99%

“…17, no. 2 / 2021 / Bogotá D.C., Colombia Universidad Cooperativa de Colombia Impact Of Structure On Team Performance applied in medical diagnostic processes, software development, translation of applications to different languages in a short time, among others [3][4] [5][6] [7] [43].…”

Section: Introductionmentioning

confidence: 99%

Impact of structure on team performance

González

Lopez²,

Arévalo³

2021

ing. Solidar

View full text Add to dashboard Cite

show abstract

“…Additionally, CPN Tools have been used to make quantitative analysis of events produced for this case study. Given the flexibility provided by MEdit4CEP-CPN, this analysis could be applied to other cutting-edge real-world case studies, such as eHealth [49], robotic [50] and mobile edge, and cloud computing applications [51].…”

Section: Discussionmentioning

confidence: 99%

Facilitating the Quantitative Analysis of Complex Events through a Computational Intelligence Model-Driven Tool

D́ıaz

Macià

Valero

et al. 2019

Scientific Programming

View full text Add to dashboard Cite

Complex event processing (CEP) is a computational intelligence technology capable of analyzing big data streams for event pattern recognition in real time. In particular, this technology is vastly useful for analyzing multicriteria conditions in a pattern, which will trigger alerts (complex events) upon their fulfillment. However, one of the main challenges to be faced by CEP is how to define the quantitative analysis to be performed in response to the produced complex events. In this paper, we propose the use of the MEdit4CEP-CPN model-driven tool as a solution for conducting such quantitative analysis of events of interest for an application domain, without requiring knowledge of any scientific programming language for implementing the pattern conditions. Precisely, MEdit4CEP-CPN facilitates domain experts to graphically model event patterns, transform them into a Prioritized Colored Petri Net (PCPN) model, modify its initial marking depending on the application scenario, and make the quantitative analysis through the simulation and monitor capabilities provided by CPN tools.

show abstract

pRankAggreg: A fast clustering based partial rank aggregation

Gao

2019

Information Sciences

View full text Add to dashboard Cite

Collective intelligence and databases in eHealth: A survey1

Cited by 8 publications

References 50 publications

Impact of structure on team performance

Impact of structure on team performance

Facilitating the Quantitative Analysis of Complex Events through a Computational Intelligence Model-Driven Tool

pRankAggreg: A fast clustering based partial rank aggregation

Contact Info

Product

Resources

About