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DC Field | Value | Language |
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dc.contributor.author | Garg, Lalit | - |
dc.contributor.author | Masala, Giovanni | - |
dc.contributor.author | McClean, Sally | - |
dc.contributor.author | Micocci, Marco | - |
dc.contributor.author | Cannas, Giuseppina | - |
dc.date.accessioned | 2017-12-20T12:53:47Z | - |
dc.date.available | 2017-12-20T12:53:47Z | - |
dc.date.issued | 2012 | - |
dc.identifier.citation | Garg, L., Masala, G., McClean, S. I., Micocci, M., & Cannas, G. (2012). Using phase type distributions for modelling HIV disease progression. 25th International Symposium on Computer-Based Medical Systems, Rome. 1-4. | en_GB |
dc.identifier.uri | https://www.um.edu.mt/library/oar//handle/123456789/24936 | - |
dc.description.abstract | Disease progression models are useful tools for gaining a systems' understanding of the transitions to disease states, and characterizing the relationship between disease progress and factors affecting it such as patients' profile, treatment and the HIV diagnosis stage. Patients are classified into four states (based on CD4+ T-lymphocyte count) and all the transitions are allowed. Examinations to identify disease progression of the patient are carried out routinely throughout the follow-up period. Therefore, the times spent at the various HIV infection stages are interval censored or right censored. This makes difficult to use simple statistical methods such as regression to model the disease progression and its relationship with the diagnosis stage. We present a novel, more intuitive and realistic approach based on phase type distributions to model progression of HIV infection and the effects and prognostic significance of HIV diagnosis stage. The approach is illustrated using a real database of total 2,092 HIV infected patients enrolled in the Italian public structures from January 1996 to January 2008. The approach can also be used to examine the effect of other covariates such as patient's profile. | en_GB |
dc.language.iso | en | en_GB |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | 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 | Using phase type distributions for modelling HIV disease progression | en_GB |
dc.type | conferenceObject | 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.bibliographicCitation.conferencename | 25th International Symposium on Computer-Based Medical Systems | en_GB |
dc.bibliographicCitation.conferenceplace | Rome, Italy, 20-22/06/2012 | en_GB |
dc.description.reviewed | peer-reviewed | en_GB |
dc.identifier.doi | 10.1109/CBMS.2012.6266408 | - |
Appears in Collections: | Scholarly Works - FacICTCIS |
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06266408.pdf Restricted Access | 214.74 kB | Adobe PDF | View/Open Request a copy |
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