Article
Predicting Risk of Adverse Outcomes in Knee Replacement Surgery with Reconstructability Analysis
Systems Science Faculty Publications and Presentations
Document Type
Post-Print
Publication Date
1-1-2017
Subjects
- Total knee replacement -- Complications,
- Health risk assessment,
- Reconstructability Analysis,
- Information Theory,
- Probabilistic graphical modeling,
- Multivariate analysis discrete multivariate modeling,
- Data mining
Disciplines
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.
DOI
10.1109/SSCI.2017.8280870
Persistent Identifier
https://archives.pdx.edu/ds/psu/26694
Citation Information
Cecily Corrine Froemke and Martin Zwick. "Predicting Risk of Adverse Outcomes in Knee Replacement Surgery with Reconstructability Analysis" (2017) Available at: http://works.bepress.com/martin_zwick/87/
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