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Permanent link (DOI): https://doi.org/10.7939/R3GD9R

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On the Application of Multi-Class Classification in Physical Therapy Recommendation Open Access

Descriptions

Other title
Subject/Keyword
Class Imbalance
Recommendation System
Physical Therapy
Multi-Class Classification
Type of item
Thesis
Degree grantor
University of Alberta
Author or creator
Zhang, Jing
Supervisor and department
Gross, Douglas (Physical Therapy)
Zaiane, Osmar (Computing Science)
Examining committee member and department
Gross, Douglas (Physical Therapy)
Bulitko, Vadim (Computing Science)
Beach, Jeremy (Medicine)
Zaiane, Osmar (Computing Science)
Department
Department of Computing Science
Specialization

Date accepted
2012-09-27T13:52:55Z
Graduation date
2012-09
Degree
Master of Science
Degree level
Master's
Abstract
Selecting appropriate rehabilitation treatments for injured workers has been a challenging task for clinicians and health care funders. Currently, clinicians are unable to identify the optimal treatment for a patient with absolute confidence and are looking for assistance from other research fields, such as Machine Learning. This thesis aims at building a knowledge-based clinical decision support system using machine learning algorithms. We have found that with proper data preprocessing, the RIPPER algorithm can extract meaningful, editable and interpretable decision rules from a severely imbalanced multi-class clinical dataset. Moreover, the extracted rule set is integrated into our prototype Work Assessment Triage Tool (WATT), a web-based online decision support system. It has an easy-to-use interface and provides useful recommendations to help clinicians make better decisions.
Language
English
DOI
doi:10.7939/R3GD9R
Rights
Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of these terms. The author reserves all other publication and other rights in association with the copyright in the thesis and, except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.
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