It is important to model progression of a disease to understanding if the patient's condition is improving or getting worse. In the case of HIV disease, the change in the patient's CD4+ T cell count is used to calculate the progression of HIV disease i.e. if the CD4 count goes down it represent the progression of the patient's HIV disease. Due to the lack of an effective cure for HIV disease, it is crucial to monitor the disease progression to managing HIV disease effectively. Therefore, this study is aimed to model HIV disease progression by using phase type survival trees to cluster patients into homogenous groups based on their disease progression to understand the effect of different factors of prognostic significance and their interactions affecting the disease progression. The proposed methods are evaluated using an empirical data of 1,838 HIV-infected patients. The methods developed in this study can also be used for modelling the progression of other chronic conditions or diseases.

Applications of phase type survival trees in HIV disease progression modelling

Masala, Giovanni;
2017

Abstract

It is important to model progression of a disease to understanding if the patient's condition is improving or getting worse. In the case of HIV disease, the change in the patient's CD4+ T cell count is used to calculate the progression of HIV disease i.e. if the CD4 count goes down it represent the progression of the patient's HIV disease. Due to the lack of an effective cure for HIV disease, it is crucial to monitor the disease progression to managing HIV disease effectively. Therefore, this study is aimed to model HIV disease progression by using phase type survival trees to cluster patients into homogenous groups based on their disease progression to understand the effect of different factors of prognostic significance and their interactions affecting the disease progression. The proposed methods are evaluated using an empirical data of 1,838 HIV-infected patients. The methods developed in this study can also be used for modelling the progression of other chronic conditions or diseases.
9781538638934
AIDS; Disease progression modelling; HIV disease progression; Phase type survival trees; Artificial Intelligence; Computer Networks and Communications; Modeling and Simulation; Computer Science Applications1707 Computer Vision and Pattern Recognition
File in questo prodotto:
File Dimensione Formato  
IEEE_2017_Masala.pdf

accesso aperto

Tipologia: versione editoriale
Dimensione 599.45 kB
Formato Adobe PDF
599.45 kB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11584/246609
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 1
  • ???jsp.display-item.citation.isi??? 0
social impact