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Permanent link (DOI): https://doi.org/10.7939/R3PR7N26Z

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Clinical Practice Guideline Formalization: Translating Clinical Practice Guidelines to Computer Interpretable Guidelines Open Access

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Other title
Subject/Keyword
Clinical Practice Guideline Formalization
Type of item
Thesis
Degree grantor
University of Alberta
Author or creator
Gad El-Rab, Wessam
Supervisor and department
El-Hajj, Mohammad (MacEwan University - Computer Science)
Zaïane, Osmar (Computing Science)
Examining committee member and department
Kondrak, Greg (Computing Science)
Reda Alhajj (University of Calgary, Computer Science)
Goebel, Randy (Computing Science)
Elmallah, Ehab (Computing Science)
Department
Department of Computing Science
Specialization

Date accepted
2016-03-08T14:53:02Z
Graduation date
2016-06
Degree
Doctor of Philosophy
Degree level
Doctoral
Abstract
Clinical Practice Guidelines (CPGs) offer concise instruction on the optimal care for the patient based on the latest clinical findings. The main benefit of a CPG is to improve the quality of care, and the consistency of care. It is been shown that passive dissemination of CPGs, like publishing in a medical journal, is ineffective in changing practice behavior. Nevertheless, integrating CPG knowledge into clinical systems, such as decision support systems, has shown to be more effective. In order to best benefit from the knowledge in the CPGs, an interest in automatically formalizing medical knowledge contained in CPGs has grown. This dissertation describes a new framework to automate a subset of the common CPGs formalization research problems. Our framework follows a multi-step approach, which has been shown to be a good strategy for CPG formalization. One of the major sub-problem to automate the formalization of CPGs is to detect ambiguity in CPGs and resolve it automatically. In this dissertation we described two unsupervised algorithms to the resolve ambiguities in CPGs.
Language
English
DOI
doi:10.7939/R3PR7N26Z
Rights
This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for the purpose of private, scholarly or scientific research. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.
Citation for previous publication
Wessam Gad El-Rab, Osmar R Zaïane, and Mohammad El-Hajj. Analyzing the Impact of UMLS Relations on Word-sense Disambiguation Accuracy. Procedia Computer Science, 21:295–301, 2013.Wessam Gad El-Rab, Osmar R Zaïane, and Mohammad El-Hajj. Biomedical text disambiguation using UMLS. In Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, pages 943–947. ACM, 2013.Wessam Gad El-Rab, Osmar R Zaïane, and Mohammad El-Hajj. Unsupervised Graph-based Word Sense Disambiguation of Biomedical Documents. In e-Health Networking, Applications Services (Healthcom), 2013 IEEE 15th International Conference on, pages 649–652. IEEE, 2013.Wessam Gad El-Rab, Osmar R Zaiane and Mohammad El-Hajj, Formalizing Clinical Practice Guideline for Clinical Decision Support Systems, Journal of Health Informatics (JHI), January 2016.

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