The use of data mining techniques to predict mortality and length of stay in an ICU

Alramzana Nujum Navaz, Elfadil Mohammed, Mohamed Adel Serhani, Nazar Zaki

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)

Abstract

Data mining is commonly used in the healthcare industry and managing Intensive Care Unit (ICU) is no exception. This study aims to examine how data mining techniques can be employed to predict mortality and length of stay in an ICU and to evaluate various classification techniques. Real-life healthcare datasets, like MIMIC 2, incorporate an unbalanced distribution of sample sizes, which means that it is difficult to employ them to assess classification. This paper presents an analysis of a mortality prediction algorithm to evaluate the extent to which this algorithm can predict mortality rate. The model aims to facilitate the process by which medical practitioners provide customized and optimized care in the ICU.

Original languageEnglish
Title of host publicationProceedings of the 2016 12th International Conference on Innovations in Information Technology, IIT 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509053438
DOIs
Publication statusPublished - Mar 16 2017
Event12th International Conference on Innovations in Information Technology, IIT 2016 - Al Ain, United Arab Emirates
Duration: Nov 28 2016Nov 29 2016

Publication series

NameProceedings of the 2016 12th International Conference on Innovations in Information Technology, IIT 2016

Other

Other12th International Conference on Innovations in Information Technology, IIT 2016
Country/TerritoryUnited Arab Emirates
CityAl Ain
Period11/28/1611/29/16

Keywords

  • Data mining
  • ICU
  • MIMIC 2
  • Mortality Prediction
  • eHealth

ASJC Scopus subject areas

  • Computer Science Applications
  • Hardware and Architecture
  • Information Systems
  • Computer Networks and Communications
  • Instrumentation

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