Application of the Bayesian network on the mutual relation of influencing factors and AIDS pathogenesis.
- Author:
Na ZHANG
1
;
Guoyong WANG
;
Xiaoyan ZHU
;
Xingguang YANG
;
Dianmin KANG
2
Author Information
- Publication Type:Journal Article
- MeSH: Acquired Immunodeficiency Syndrome; drug therapy; epidemiology; pathology; Adolescent; Adult; Aged; Aged, 80 and over; Bayes Theorem; Child; Child, Preschool; China; epidemiology; Female; Humans; Incidence; Lymphocyte Count; Male; Middle Aged; Young Adult
- From: Chinese Journal of Preventive Medicine 2014;48(4):296-300
- CountryChina
- Language:Chinese
-
Abstract:
OBJECTIVETo explore the influencing factors of AIDS pathogenesis using the Bayesian network.
METHODSBased on follow-up data of 2 431 cases of HIV/AIDS from 1992-2011 in Shandong province, this study constructed the network structure by NPC algorithm, and used the EM algorithm for parameter learning to construct the Bayesian network of influencing factors and AIDS pathogenesis, then did inference by the Bayesian network.
RESULTSA total of 49.77% (1 210/2 431) were AIDS. Get a Bayesian network with 7 nodes and 11 directed arcs and the related parameters by studying the follow-up data of 2 431 cases. The area under receiver operating curve(ROC) was 0.75. There was a direct causal association among sample resource, transmission route, CD4(+)T lymphocyte count of HIV-antibody confirmed positive, antiviral therapy, opportunistic infection therapy, follow-up intervention and AIDS pathogenesis. The incidence probability was 42.83% for those who received antiviral therapy and follow-up intervention, and it was 68.96% for those who received antiviral therapy without follow-up intervention. The probability to receive follow-up intervention was 68.96% for cases transmitted by homosexual behaviors, and it was 34.00%, 42.24%, 1.06% and 22.70% respectively to be reported by medical institutions, testing and counselling, supervision institutions and special surveys.
CONCLUSIONThe Bayesian network revealed the mutual relation and effect intension among multi-factors and multi-stages by network inference. It showed that the rate of AIDS pathogenesis was lower for those who received antiviral therapy and follow-up intervention.
