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Computational Molecular Biology
2014, Vol.4, No.3, 26-33 http://cmb.biopublisher.ca
Research Report
Open Access
Association Rules for Diagnosis of Hiv-Aids
Anubha Dubey
Department of Bioinformatics, MANIT, BHOPAL, India
Corresponding Author email: anubhadubey@rediffmail.com;
Author
Computational Molecular Biology, 2014, Vol.4, No.3 doi: 10.5376/cmb.2014.04.0003
Copyright
© 2014 Dubey. This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use,
distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
Association rule mining is an active area of research in data mining. Data mining is a process of finding patterns from
very large volumes of data. These patterns are important in making association rules and correlations among them. Recent years have
witnessed many efforts on discovering associations for genes, proteins, enzymes, networks. In this study, association rules for HIV
disease diagnosis is tried to generate. It describes the concept of different stages of HIV progression which are associated with other
infections. As huge patient data is available, there is a need to develop some interesting patterns, associations, correlations for proper
treatment and disease diagnosis. The efficiency and advantages of these rules has been used by medical practioners to diagnose the
disease or recommend the suitable treatment.
Keywords
Associations; Correlations; Pattern; HIV; Treatment
1 Introduction
HIV causes AIDS the life threatening opportunistic
infection which leads to death of an individual. HIV
infections are considered pandemic by the World
Health Organization (WHO).
As of 2010
approximately 34 million people have HIV globally.
Of these approximately 16.8 million are women and
3.4 million are less than 15 years old. It resulted in
about 1.8 million deaths in 2010, down from 3.1
million in 2001 (UNAIDS, 2010).
HIV infects primarily vital cells in the human immune
system such as helper T cells (specifically, CD4
+
T
cells), macrophages, and dendritic cells. HIV infection
leads to low levels of CD4
+
T cells through three main
mechanisms: (a) direct viral killing of infected cells;
(b) increased rates of apoptosis in infected cells; and
(c) killing of infected CD4
+
T cells by CD8 cytotoxic
lymphocytes that recognize infected cells. When CD4
+
T cell numbers decline below a critical level,
cell-mediated immunity is lost, and the body becomes
progressively more susceptible to opportunistic
infections.
1.1 Classification of HIV
Two types of HIV have been characterized: HIV-1
and HIV-2. HIV-1 is the virus that was initially
discovered and termed both LAV and HTLV-III. It
is more virulent, more infective and is the cause of
the majority of HIV infections globally (Gilbert et
al., 2003). HIV-1 is originated from Common
Chimpanzee and HIV is originated from Sooty
Mangabey (Smm). The lower infectivity of HIV-2
compared to HIV-1 implies that fewer of those
exposed to HIV-2 will be infected per exposure.
Because of its relatively poor capacity for
transmission, HIV-2 is largely confined to West
Africa (Reeves and Doms, 2002).
Both HIV-1 and HIV-2 are believed to have
originated in West-Central Africa and to have
jumped species (a process known as zoonosis) from
non-human primates to humans (Sharp and Hahn,
2011). AIDS was first clinically observed in 1981
in the United States (Kaiser, 2008). In 1983, two
separate research groups led by Robert Gallo and
Luc Montagnier independently declared that a novel
Preferred citation for this article:
Anubha Dubey, 2014, Association Rules for Diagnosis of Hiv-Aids, Computational Molecular Biology, Vol.4, No.3 26-33 (doi: 10.5376/cmb.2014.04.0003)
Received: 04 Mar., 2014
|
Accepted: 15 Apr., 2014
|
Published: 01 May., 2014
Computational
Molecular Biology