Clinical Decision Support System with Adaptive Software Framework for Chronic Lymphocytic Leukaemia Cell Classification

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atmire.migration.oldid1343
dc.contributor.advisorFar, Behrouz
dc.contributor.advisorNaugler, Christopher
dc.contributor.authorMohammed, Emad
dc.date.accessioned2013-09-16T19:56:41Z
dc.date.available2013-11-12T08:00:17Z
dc.date.issued2013-09-16
dc.date.submitted2013en
dc.description.abstractThis thesis presents a new clinical decision support system (CDSS), which operates within an adaptive software framework and a tailored wrapper design pattern for chronic lymphocytic leukaemia (CLL) cell classification. The system goes through a sequence of steps while working with the lymphocyte images: it segments the lymphocyte with average segmentation accuracy of (97% ±0.5 for lymphocyte nucleus and 92.08% ±9.24 for lymphocyte cytoplasm); it extracts features; it selects from those features the relevant ones; and, it then classifies the selected features. The proposed system composite classifier model has a trust factor of 84.16%, accuracy of 87.0%, 84.95% true positive rate, and 10.96% false positive rate. The framework along with the wrapper pattern became a generic interface for any new algorithm. The framework built on top of the data-centric architecture which provides a great flexibility to the system design. The wrapper verifies the new algorithm interface against built-in test procedures.en_US
dc.identifier.citationMohammed, E. (2013). Clinical Decision Support System with Adaptive Software Framework for Chronic Lymphocytic Leukaemia Cell Classification (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. doi:10.11575/PRISM/25333en_US
dc.identifier.doihttp://dx.doi.org/10.11575/PRISM/25333
dc.identifier.urihttp://hdl.handle.net/11023/976
dc.language.isoeng
dc.publisher.facultyGraduate Studies
dc.publisher.institutionUniversity of Calgaryen
dc.publisher.placeCalgaryen
dc.rightsUniversity of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.
dc.subjectBiomedical
dc.subject.classificationClinical Decision Support System (CDSS)en_US
dc.subject.classificationMachine Learningen_US
dc.subject.classificationAdaptive Software Frameworken_US
dc.subject.classificationClassifier Fusionen_US
dc.subject.classificationDempster-Shafer Theoryen_US
dc.subject.classificationTailored Wrapper Design Patternen_US
dc.subject.classificationChronic Lymphocytic Leukaemia (CLL)en_US
dc.subject.classificationBioinformaticsen_US
dc.subject.classificationWhite Blood Cellsen_US
dc.subject.classificationData Miningen_US
dc.titleClinical Decision Support System with Adaptive Software Framework for Chronic Lymphocytic Leukaemia Cell Classification
dc.typemaster thesis
thesis.degree.disciplineElectrical and Computer Engineering
thesis.degree.grantorUniversity of Calgary
thesis.degree.nameMaster of Science (MSc)
ucalgary.item.requestcopytrue
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