Predicting Risk of Adverse Outcomes in Knee Replacement Surgery with Reconstructability Analysis

Authors

Cecily Corrine Froemke, Portland State UniversityFollow
Martin Zwick, Portland State UniversityFollow

Document Type

Post-Print

Publication Date

2017

Subjects

Total knee replacement -- Complications, Health risk assessment, Reconstructability Analysis, Information Theory, Probabilistic graphical modeling, Multivariate analysis discrete multivariate modeling, Data mining

Abstract

Reconstructability Analysis (RA) is a data mining method that searches for relations in data, especially non-linear and higher order relations. This study shows that RA can provide useful predictions of complications in knee replacement surgery.

Description

This is an Accepted Manuscript of an article published by IEEE in 2017 in IEEE Symposium Series on Computational Intelligence (SSCI). The definitive version is available here: https://doi.org/10.1109/SSCI.2017.8280870

DOI

10.1109/SSCI.2017.8280870

Persistent Identifier

https://archives.pdx.edu/ds/psu/26694

Citation Details

Froemke, Cecily Corrine and Zwick, Martin, "Predicting Risk of Adverse Outcomes in Knee Replacement Surgery with Reconstructability Analysis" (2017). Systems Science Faculty Publications and Presentations. 127.
https://archives.pdx.edu/ds/psu/26694