A fuzzy discrete event system for HIV/AIDS treatment planning

Treatment decision-making for most diseases is currently partial art and partial science. To a large extent, this is due to the fact that every patient is unique, and many symptoms and diagnoses are inherently imprecise and difficult to measure. A systematic decision-making and optimization technology capable of handling all the clinical difficulties is still unavailable despite significant efforts documented in the literature, including the use of artificial intelligence and statistical methods. One promising approach is the novel fuzzy discrete event systems whose theoretical framework was recently developed by us. In this paper, we apply it to treatment planning for HIV/AIDS patients who have never received antiretroviral therapy. We show how to design such a system. We have also statistically evaluated the preliminary results produced by the system in comparison with two AIDS specialists on our team. The results indicate strong agreement between the physicians and the fuzzy discrete event system. This is the first application of fuzzy discrete event systems in the l iterature.