Stabilizing high-dimensional prediction models using feature graphs

Gopakumar, Shivapratap, Tran, Truyen, Nguyen, Tu Dinh, Phung, Dinh and Venkatesh, Svetha 2015, Stabilizing high-dimensional prediction models using feature graphs, IEEE journal of biomedical and health informatics, vol. 19, no. 3, pp. 1044-1052, doi: 10.1109/JBHI.2014.2353031.

Attached Files
Name Description MIMEType Size Downloads

Title Stabilizing high-dimensional prediction models using feature graphs
Author(s) Gopakumar, Shivapratap
Tran, TruyenORCID iD for Tran, Truyen orcid.org/0000-0001-6531-8907
Nguyen, Tu Dinh
Phung, DinhORCID iD for Phung, Dinh orcid.org/0000-0002-9977-8247
Venkatesh, SvethaORCID iD for Venkatesh, Svetha orcid.org/0000-0001-8675-6631
Journal name IEEE journal of biomedical and health informatics
Volume number 19
Issue number 3
Start page 1044
End page 1052
Total pages 9
Publisher IEEE
Place of publication Champaign, III.
Publication date 2015-05
ISSN 2168-2208
Keyword(s) Aged
Electric Health Records
Female
Heart Failure
Humans
Male
Models, Biological
Models, Statistical
Reproductility of Results
Risk Factors
Summary We investigate feature stability in the context of clinical prognosis derived from high-dimensional electronic medical records. To reduce variance in the selected features that are predictive, we introduce Laplacian-based regularization into a regression model. The Laplacian is derived on a feature graph that captures both the temporal and hierarchic relations between hospital events, diseases, and interventions. Using a cohort of patients with heart failure, we demonstrate better feature stability and goodness-of-fit through feature graph stabilization.
Language eng
DOI 10.1109/JBHI.2014.2353031
Field of Research 080109 Pattern Recognition and Data Mining
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category C1 Refereed article in a scholarly journal
Copyright notice ©2015, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30076886

Document type: Journal Article
Collections: Centre for Pattern Recognition and Data Analytics
2018 ERA Submission
Connect to link resolver
 
Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved.

Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 1 times in TR Web of Science
Scopus Citation Count Cited 3 times in Scopus
Google Scholar Search Google Scholar
Access Statistics: 287 Abstract Views, 4 File Downloads  -  Detailed Statistics
Created: Tue, 01 Mar 2016, 11:11:08 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.