Instance Selection Algorithms for Predictive Modelling in Telehealth Applications

Fabian Wiesmüller, Dieter Hayn, Florian Hoffmann, Sten Hanke, Peter Kastner, Markus Falgenhauer, Günter Schreier

Publikation: Beitrag in Buch oder TagungsbandVortrag mit Beitrag in TagungsbandBegutachtung

Abstract

Telehealth services are becoming more and more popular, leading to an increasing amount of data to be monitored by health professionals. Machine learning can support them in managing these data. Therefore, the right machine learning algorithms need to be applied to the right data. We have implemented and validated different algorithms for selecting optimal time instances from time series data derived from a diabetes telehealth service. Intrinsic, supervised, and unsupervised instance selection algorithms were analysed. Instance selection had a huge impact on the accuracy of our random forest model for dropout prediction. The best results were achieved with a One Class Support Vector Machine, which improved the area under the receiver operating curve of the original algorithm from 69.91 to 75.88 %. We conclude that, although hardly mentioned in telehealth literature so far, instance selection has the potential to significantly improve the accuracy of machine learning algorithms.

OriginalspracheEnglisch
TitelMedInfo 2023: The 19th World Congress on Medical and Health Informatics
Redakteure/-innenJen Bichel-Findlay, Paula Otero, Philip Scott, Elaine Huesing
Herausgeber (Verlag)IOS Press BV
Seiten840-844
Seitenumfang5
Band310
ISBN (elektronisch)978-1-64368-457-4
ISBN (Print) 978-1-64368-456-7
DOIs
PublikationsstatusVeröffentlicht - 25 Jan. 2024
VeranstaltungMedInfo 2023: THE FUTURE IS ACCESSIBLE - International Convention Centre (ICC), Sydney, Australien
Dauer: 8 Juli 202312 Juli 2023
Konferenznummer: 19.
https://medinfo2023.org/

Konferenz

KonferenzMedInfo 2023: THE FUTURE IS ACCESSIBLE
KurztitelMedInofo 2023
Land/GebietAustralien
StadtSydney
Zeitraum8/07/2312/07/23
Internetadresse

Research Field

  • Exploration of Digital Health

Fingerprint

Untersuchen Sie die Forschungsthemen von „Instance Selection Algorithms for Predictive Modelling in Telehealth Applications“. Zusammen bilden sie einen einzigartigen Fingerprint.

Diese Publikation zitieren