Wen Yan

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Leprosy is a disabling chronic infection, with insidious onset that often evades early detection. In order to detect new leprosy cases in a timely manner, we conducted surveillance visits in some difficult-to-reach mountain areas in South West China where the disease is still prevalent. Our data confirm that Chinese multibacillary (MB) leprosy patients have(More)
Pawlak recently introduced rough set flow graphs (RSFGs) as a graphical framework for reasoning from data. Each rule is associated with three coefficients, which have been shown to satisfy Bayes' theorem. Thereby, RSFGs provide a new perspective on Bayesian inference methodology. In this paper, we show that inference in RSFGs takes polynomial time with(More)
We show that a conditional probability table (CPT) is obtained after every multiplication and every marginalization step when eliminating variables from a discrete Bayesian network. The main advantage of our work is an improvement in presentation. The probability distributions constructed during variable elimination in Bayesian networks have always been(More)
We present an algorithm, called Semantics in Inference (SI), that uses d-separation to denote the semantics of every potential constructed during exact inference in discrete Bayesian networks. We establish that SI possesses four salient features, namely, polynomial time complexity, soundness, completeness, and strong completeness. SI provides a better(More)
PURPOSE Texture patterns of hepatic fibrosis are one of the important biomarkers to diagnose and classify chronic liver disease from initial to end stage on computed tomography (CT) or magnetic resonance (MR) images. Computer-aided diagnosis (CAD) of liver cirrhosis using texture features has become popular in recent research advances. To date, however,(More)