DataCare: Big Data Analytics Solution for Intelligent Healthcare Management

dc.contributor.authorSaez, Yago
dc.contributor.authorBaldominos Gómez, Alejandro
dc.contributor.authorRada, Fernando
dc.date2018-03
dc.date.accessioned2021-09-27T09:37:40Z
dc.date.available2021-09-27T09:37:40Z
dc.description.abstractThis paper presents DataCare, a solution for intelligent healthcare management. This product is able not only to retrieve and aggregate data from different key performance indicators in healthcare centers, but also to estimate future values for these key performance indicators and, as a result, fire early alerts when undesirable values are about to occur or provide recommendations to improve the quality of service. DataCare’s core processes are built over a free and open-source cross-platform document-oriented database (MongoDB), and Apache Spark, an open-source cluster-computing framework. This architecture ensures high scalability capable of processing very high data volumes coming at fast speed from a large set of sources. This article describes the architecture designed for this project and the results obtained after conducting a pilot in a healthcare center. Useful conclusions have been drawn regarding how key performance indicators change based on different situations, and how they affect patients’ satisfaction.es_ES
dc.identifier.doihttp://doi.org/10.9781/ijimai.2017.03.002
dc.identifier.issn1989-1660
dc.identifier.urihttps://reunir.unir.net/handle/123456789/11904
dc.language.isoenges_ES
dc.publisherInternational Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI)es_ES
dc.relation.ispartofseries;vol. 4, nº 7
dc.relation.urihttps://www.ijimai.org/journal/bibcite/reference/2614es_ES
dc.rightsopenAccesses_ES
dc.subjectartificial intelligencees_ES
dc.subjectarchitecturees_ES
dc.subjectmanagemet systemses_ES
dc.subjectbig dataes_ES
dc.subjecte-healthes_ES
dc.subjectIJIMAIes_ES
dc.titleDataCare: Big Data Analytics Solution for Intelligent Healthcare Managementes_ES
dc.typearticlees_ES
reunir.tag~IJIMAIes_ES

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