Exploring the Important Attributes of Human Immunodeficiency Virus and Generating Decision Rules

被引:1
作者
Cheng, Ching-Hsue [1 ]
Wang, Yun-Chun [1 ]
机构
[1] Natl Yunlin Univ Sci & Technol, Dept Informat Management, 123 Univ Rd,Sect 3, Touliu 64002, Yunlin, Taiwan
来源
SYMMETRY-BASEL | 2020年 / 12卷 / 01期
关键词
Acquired Immunodeficiency Syndrome (AIDS); Human Immunodeficiency Virus (HIV); attribute selection; rough set classifier; recency; frequency; and monetary (RFM); BASIS FUNCTION NETWORKS; FEATURE-SELECTION; RANDOM FOREST; IDENTIFICATION; CLASSIFICATION; TREE; AIDS; HIV;
D O I
10.3390/sym12010067
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Acquired Immunodeficiency Syndrome (AIDS) is the most severe phase of Human Immunodeficiency Virus (HIV) infection. Living with HIV results in a weakened immune system, with AIDS being the final stage of HIV and puzzling the world. The current medical environment remains unable to effectively cure AIDS, with treatment depending on long-term antiretroviral therapy (ART). To effectively treat and prevent HIV, it is important to elucidate the key factors of HIV propagation. This study proposes a rough set classifier based on adding recency (R) (i.e., the last physician visit), frequency (F) (i.e., the frequency of medical visits), and monetary (M) (i.e., medication adherence) attributes and integrated attribute selection methods to generate discriminatory rules and find the core attributes of HIV. The collected data consist of 1308 HIV infection records from Taiwan. From the experimental results, the frequency of CD4+ cells in the peripheral blood is able to determine patient medication, treatment willingness, and HIV infection stages, because HIV patients are less likely to be willing to receive long-term ART. Furthermore, drug abuse is found to be the greatest cause of HIV infection. These results show that the additional RFM attributes can improve classification accuracy, with the core attributes being M, R, plasma viral load (PVL) and age. Hence, we suggest that clinical physicians use these core attributes to understand the HIV infection stages.
引用
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页数:15
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