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DC Field | Value | Language |
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dc.date.accessioned | 2016-07-11T10:48:34Z | - |
dc.date.available | 2016-07-11T10:48:34Z | - |
dc.date.issued | 2015 | - |
dc.identifier.uri | https://www.um.edu.mt/library/oar//handle/123456789/11376 | - |
dc.description | B.SC.IT(HONS) | en_GB |
dc.description.abstract | Disease progression models are useful tools in analysing disease progression where HIV disease is termed as progressing if the CD4 count goes down. This is because the CD4+ T cell count is used as the main predictor of HIV disease progression and patients are classified into four states based on this count. Currently no effective cure for HIV disease exists and monitoring closely the disease progression is crucial. Hence, the aim of this dissertation is to model progression of HIV disease by clustering and quantifying the effects of several covariates and their interaction in the prediction of HIV disease progression using phase type survival trees. This is done by using a real database of 1,838 HIV infected patients and as a result the covariates which have prognostic significance on the disease progression are identified. The outcome of this research work should aid to effectively manage HIV disease, while the methods developed can also be useful for modelling disease progression in patients who have other chronic conditions or diseases. | en_GB |
dc.language.iso | en | en_GB |
dc.rights | info:eu-repo/semantics/restrictedAccess | en_GB |
dc.subject | Markov processes | en_GB |
dc.subject | AIDS (Disease) | en_GB |
dc.subject | T cells | en_GB |
dc.title | HIV disease progression modelling using phase type survival trees | en_GB |
dc.type | bachelorThesis | en_GB |
dc.rights.holder | The copyright of this work belongs to the author(s)/publisher. The rights of this work are as defined by the appropriate Copyright Legislation or as modified by any successive legislation. Users may access this work and can make use of the information contained in accordance with the Copyright Legislation provided that the author must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the prior permission of the copyright holder. | en_GB |
dc.publisher.institution | University of Malta | en_GB |
dc.publisher.department | Faculty of Information and Communication Technology. Department of Computer Science | en_GB |
dc.description.reviewed | N/A | en_GB |
dc.contributor.creator | Gafa`, Marija | - |
Appears in Collections: | Dissertations - FacICT - 2015 Dissertations - FacICTCS - 2010-2015 |
Files in This Item:
File | Description | Size | Format | |
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15BSCIT047.pdf Restricted Access | 2.11 MB | Adobe PDF | View/Open Request a copy |
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