Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/51581

TitlePatients' admissions in intensive care units: a clustering overview
Author(s)Ribeiro, Ana
Portela, Filipe
Santos, Manuel
Abelha, António
Machado, José Manuel
Rua, Fernando
KeywordsAdmissions
Clustering
Data mining
Decision support systems
INTCare system
Intensive care
Issue date17-Feb-2017
PublisherMDPI
JournalInformation
Abstract(s)Intensive care is a critical area of medicine having a multidisciplinary nature requiring all types of healthcare professionals. Given the critical environment of intensive care units (ICUs), the need to use information technologies, like decision support systems, to improve healthcare services and ICU management is evident. It is proven that unplanned and prolonged admission to the ICU is not only prejudicial to a patient's health, but also such a situation implies a readjustment of ICU resources, including beds, doctors, nurses, financial resources, among others. By discovering the common characteristics of the admitted patients, it is possible to improve these outcomes. In this study clustering techniques were applied to data collected from admitted patients in an intensive care unit. The best results presented a silhouette of 1, with a distance to centroids of 6.2 × 10 -17 and a Davies-Bouldin index of -0.652.
TypeArticle
URIhttp://hdl.handle.net/1822/51581
DOI10.3390/info8010023
ISSN2078-2489
Peer-Reviewedyes
AccessOpen access
Appears in Collections:CAlg - Artigos em revistas internacionais/Papers in international journals

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