<p> The constantly changing and dynamic nature of medical knowledge has proven to be
challenging for healthcare professionals. Due to reliance on human knowledge the practice
of medicine in many cases is subject to errors that endanger patients' health and cause
substantial financial loss to both public and governmental health sectors. Computer
based clinical guidelines have been developed to help healthcare professionals in practicing
medicine. Currently, the decision making steps within most guideline modeling languages
are limited to the evaluation of basic logic expressions. On the other hand, data mining
analyses aim at building descriptive or predictive mining models that contain valuable
knowledge; and researchers in this field have been active to apply data mining techniques
on health data. However, this type of knowledge can not be represented using the current
guideline specification standards.</p> <p> In this thesis, we focus is on encoding, sharing and finally using the results obtained from a data mining study in the context of clinical care and in particular at the point of care. For this purpose, a knowledge management framework is proposed that addresses the issues of data and knowledge interoperability. Standards are adopted to represent both data and data mining results in an interoperable manner; and then the incorporation of data mining results into guideline-based Clinical Decision Support Systems is elaborated. A prototype tool has been developed as a part of this thesis that serves as the proof of concept which provides an environment for clinical guideline authoring and
execution. Finally three real-world clinical case studies are presented.</p> / Thesis / Master of Applied Science (MASc)
| Identifer | oai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/21145 |
| Date | 08 1900 |
| Creators | Kazemzadeh, Reza Sherafat |
| Contributors | Sartipi, Kamran, Software Engineering |
| Source Sets | McMaster University |
| Language | en_US |
| Detected Language | English |
| Type | Thesis |
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