Abstract
This study aims to discover groups (clusters) of patient who share whole-person characteristics. An unsupervised clustering analysis using a hierarchical agglomerative approach was applied to identify meaningful groups of patient characteristics. Results showed that is possible to identify clusters that have similar patient characteristics, and that these characteristics may be associated with survival.
Original language | English (US) |
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Title of host publication | Nursing Informatics 2016 - eHealth for All |
Subtitle of host publication | Every Level Collaboration - From Project to Realization |
Editors | Walter Sermeus, Paula M. Procter, Patrick Weber |
Publisher | IOS Press BV |
Pages | 382-386 |
Number of pages | 5 |
ISBN (Electronic) | 9781614996576 |
DOIs | |
State | Published - 2016 |
Event | 13th International Conference on Nursing Informatics, NI 2016 - Geneva, Switzerland Duration: Jun 25 2016 → Jun 29 2016 |
Publication series
Name | Studies in Health Technology and Informatics |
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Volume | 225 |
ISSN (Print) | 0926-9630 |
ISSN (Electronic) | 1879-8365 |
Other
Other | 13th International Conference on Nursing Informatics, NI 2016 |
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Country/Territory | Switzerland |
City | Geneva |
Period | 6/25/16 → 6/29/16 |
Bibliographical note
Publisher Copyright:© 2016 IMIA and IOS Press.
Keywords
- Cluster analysis
- Health data
- Informatics
- Liver transplantation
- Predictors