Clustering the whole-person health data to predict liver transplant survival

Lisiane Pruinelli; Karen A Monsen; Gyorgy J Simon; Bonnie L Westra

doi:10.3233/978-1-61499-658-3-382

Clustering the whole-person health data to predict liver transplant survival

Lisiane Pruinelli, Karen A Monsen, Gyorgy J Simon, Bonnie L Westra

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

5 Scopus citations

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)
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	https://doi.org/10.3233/978-1-61499-658-3-382
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
Volume	225
ISSN (Print)	0926-9630
ISSN (Electronic)	1879-8365

Other

Other	13th International Conference on Nursing Informatics, NI 2016
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

Publisher link

10.3233/978-1-61499-658-3-382

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Pruinelli, L., Monsen, K. A., Simon, G. J., & Westra, B. L. (2016). Clustering the whole-person health data to predict liver transplant survival. In W. Sermeus, P. M. Procter, & P. Weber (Eds.), Nursing Informatics 2016 - eHealth for All: Every Level Collaboration - From Project to Realization (pp. 382-386). (Studies in Health Technology and Informatics; Vol. 225). IOS Press BV. https://doi.org/10.3233/978-1-61499-658-3-382

Clustering the whole-person health data to predict liver transplant survival. / Pruinelli, Lisiane ; Monsen, Karen A ; Simon, Gyorgy J et al.
Nursing Informatics 2016 - eHealth for All: Every Level Collaboration - From Project to Realization. ed. / Walter Sermeus; Paula M. Procter; Patrick Weber. IOS Press BV, 2016. p. 382-386 (Studies in Health Technology and Informatics; Vol. 225).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Pruinelli, L , Monsen, KA , Simon, GJ & Westra, BL 2016, Clustering the whole-person health data to predict liver transplant survival. in W Sermeus, PM Procter & P Weber (eds), Nursing Informatics 2016 - eHealth for All: Every Level Collaboration - From Project to Realization. Studies in Health Technology and Informatics, vol. 225, IOS Press BV, pp. 382-386, 13th International Conference on Nursing Informatics, NI 2016, Geneva, Switzerland, 6/25/16. https://doi.org/10.3233/978-1-61499-658-3-382

Pruinelli L , Monsen KA , Simon GJ, Westra BL. Clustering the whole-person health data to predict liver transplant survival. In Sermeus W, Procter PM, Weber P, editors, Nursing Informatics 2016 - eHealth for All: Every Level Collaboration - From Project to Realization. IOS Press BV. 2016. p. 382-386. (Studies in Health Technology and Informatics). doi: 10.3233/978-1-61499-658-3-382

Pruinelli, Lisiane ; Monsen, Karen A ; Simon, Gyorgy J et al. / Clustering the whole-person health data to predict liver transplant survival. Nursing Informatics 2016 - eHealth for All: Every Level Collaboration - From Project to Realization. editor / Walter Sermeus ; Paula M. Procter ; Patrick Weber. IOS Press BV, 2016. pp. 382-386 (Studies in Health Technology and Informatics).

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Clustering the whole-person health data to predict liver transplant survival

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