A self-learning fuzzy discrete event system for HIV/AIDS treatment regimen selection.

The U.S. Department of Health and Human Services Human Immunodeficiency Virus (HIV)/Acquired Immune Deficiency Syndrome (AIDS) treatment guidelines are modified several times per year to reflect the rapid evolution of the field (e.

A team agent approach to postmarketing surveillance of adverse drug reactions.

Current postmarketing surveillance methods largely rely on spontaneous reports which suffer from serious underreporting, latency, and inconsistent reporting. Thus they are not ideal for rapidly identifying rare adverse drug reactions (ADRs). We propose an active, multi-agent computer software system, where each agent is empowered with teamwork capabilities such as anticipating information needs, identifying relevant ADR information, and continuously monitoring and proactively sharing such information in a collaborative fashion with other agents.

A fuzzy discrete event system approach to determining optimal HIV/AIDS treatment regimens.

Treatment decision-making is complex and involves many factors. A systematic decision-making and optimization technology capable of handling variations and uncertainties of patient characteristics and physician's subjectivity is currently unavailable. We recently developed a novel general-purpose fuzzy discrete event systems theory for optimal decision-making.

Age of sexual initiation and HIV-related behaviours: application of survival analysis.

Previous studies have consistently suggested positive associations between early sexual initiation and subsequent risky sexual behaviours, HIV/STD infection, adolescent pregnancy and substance use. In the present study, survival curves for rural-to-urban migrants in China with and without HIV-related behaviours were analysed to determine (1) the risk of initiating sex at each ageand (2) the association between sexual initiation and HIV-related behaviours.