On the representation of machine learning results for delirium prediction in a hospital information system in routine care

Sai Veeranki (Vortragende:r), Dieter Hayn, Alphons Eggerth, Stefanie Jauk, Diether Kramer, Werner Leodolter, Günter Schreier

Publikation: Beitrag in Buch oder TagungsbandVortrag mit Beitrag in TagungsbandBegutachtung

Abstract

Digitalisation of health care for the purpose of medi cal documentation lead to huge amounts of data, hence having an opport unity to derive knowledge and associations of different attributes recorded. Many health care events can be prevented when identified. Machine learning algorithms could identify such events but there is ambiguity in understanding the suggestio ns especially in clinical setup. In this paper we are presenting how we explain the dec ision based on random forest to health care professionals in the course of th e project predicting delirium during hospitalisation on the day of admission.
OriginalspracheEnglisch
TitelData, Informatics and Technology: An Inspiration for Improved Health Care (Serie Studies in Health Technology and Informatics)
Herausgeber (Verlag)IOS Press
Seiten97-100
Seitenumfang4
ISBN (Print)978-1-61499-880-8
DOIs
PublikationsstatusVeröffentlicht - 2018
Veranstaltung16th International Conference on Informatics, Management and Technology in Healthcare (ICIMTH 2018) -
Dauer: 6 Juli 20188 Juli 2018

Konferenz

Konferenz16th International Conference on Informatics, Management and Technology in Healthcare (ICIMTH 2018)
Zeitraum6/07/188/07/18

Research Field

  • Exploration of Digital Health

Schlagwörter

  • Electronic health records
  • machine learning
  • delirium
  • im portant features

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