A comprehensive identification-evidence based alternative for HIV/AIDS treatment with HAART in the healthcare industries.
OBJECTIVE
The HIV/AIDS-related issue has given rise to a priority concern in which potential new therapies are increasingly highlighted to lessen the negative impact of highly active anti-retroviral therapy (HAART) in the healthcare industry. With the motivation of "medical applications," this study focuses on the main advanced feature selection techniques and classification approaches that reflect a new architecture, and a trial to build a hybrid model for interested parties.


METHODS
This study first uses an integrated linear-nonlinear feature selection technique to identify the determinants influencing HAART medication and utilizes organizations of different condition-attributes to generate a hybrid model based on a rough set classifier to study evolving HIV/AIDS research in order to improve classification performance.


RESULTS
The proposed model makes use of a real data set from Taiwan's specialist medical center. The experimental results show that the proposed model yields a satisfactory result that is superior to the listed methods, and the core condition-attributes PVL, CD4, Code, Age, Year, PLT, and Sex were identified in the HIV/AIDS data set. In addition, the decision rule set created can be referenced as a knowledge-based healthcare service system as the best of evidence-based practices in the workflow of current clinical diagnosis.


CONCLUSIONS
This study highlights the importance of these key factors and provides the rationale that the proposed model is an effective alternative to analyzing sustained HAART medication in follow-up studies of HIV/AIDS treatment in practice.
Department of Information Management, Hwa Hsia University of Technology, 111, Gongzhuan Rd., Zhonghe Dist., New Taipei City 235, Taiwan. Electronic address: ys_chen@cc.hwh.edu.tw.
You-Shyang
YS
Chen
D000328:Adult; D023241:Antiretroviral Therapy, Highly Active; D003695:Delivery of Health Care / Q000458:organization & administration*; D019317:Evidence-Based Medicine; D005260:Female; D015658:HIV Infections / Q000188:drug therapy*; D006801:Humans; D008297:Male; D008875:Middle Aged
Acquired immune deficiency syndrome (AIDS); Highly active anti-retroviral therapy (HAART); Human immunodeficiency virus (HIV); Hybrid model; Linear–nonlinear feature selection