patients’ admissions in intensive care units: a clustering overview

Clicks: 285
ID: 182289
2017
Free PDF
Article Quality & Performance Metrics
Overall Quality Improving Quality
0.0 /100
Combines engagement data with AI-assessed academic quality
AI Quality Assessment
Not analyzed
Abstract
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.
Reference Key
ribeiro2017informationpatients Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Ana Ribeiro;Filipe Portela;Manuel Santos;António Abelha;José Machado;Fernando Rua
Journal psychoanalytic review
Year 2017
DOI
10.3390/info8010023
URL
http://www.mdpi.com/2078-2489/8/1/23
Keywords
Data mining admissions clustering intensive care decision support systems

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.