Skin cancer is considered to be the most common and dangerous type of cancer. Information technology techniques are required detect diagnose skin Therefore, there a need for an early accurate diagnosis detection by employing efficient deep learning technique. This research work proposes automatic Deep Convolution Neural Network (DCNN). The distinguishing feature this it employs DCNN with 12 nes...

BACKGROUND Boceprevir and telaprevir have recently showed dramatically better treatment outcomes than conventional PEGylated interferon plus ribavirin for the treatment of hepatitis C virus genotype 1, but the average cost per patient is unknown. METHODS In the UK context, we performed a budget impact analysis to estimate the average per patient cost of adding boceprevir or telaprevir to PEGy...

This study provides operational guidance for using naïve Bayes Bayesian network (BN) models in bankruptcy prediction. First, we suggest a heuristic method that guides the selection of bankruptcy predictors from a pool of potential variables. The method is based upon the assumption that the joint distribution of the variables is multivariate normal. Variables are selected based upon correlations...

Background: Adipose derived stem cells (ASCs) provoke the accumulation and expansion of regulatory T cells, leading to the modulation of immune responses in tumor microenvironment. Objective: To assess the effect of tumoral ASCs on the trend of regulatory T cells differentiation. Methods: Peripheral blood naïve CD4+ T cells were co-cultured with ASCs derived from breast cancer or normal breast ...

Spam is commonly known as unsolicited or unwanted email messages in the Internet causing potential threat to Internet Security. Users spend a valuable amount of time deleting spam emails. More importantly, ever increasing spam emails occupy server storage space and consume network bandwidth. Keyword-based spam email filtering strategies will eventually be less successful to model spammer behavi...

We propose a Bayesian approach for estimating branching tree mixture models to compare drug-resistance pathways (i.e. patterns of sequential acquisition of resistance to individual antibiotics) that are observed among Mycobacterium tuberculosis isolates collected from treatment-naïve and treatment-experienced patients. Resistant pathogens collected from treatment-naïve patients are strains for ...

We examine the impact of glucose in a choice task that can distinguish Bayesian from lowerlevel reinforcement heuristic choice. Drawing from a dual systems framework, we hypothesize that glucose administration will increase response times and improve Bayesian accuracy because it should shift decision making towards the more deliberate system 2 and away from the more automatic system 1 decision ...

With the rapid growth of online information, text categorization has become one of the key techniques for handling and organizing text data. Though the native features of SVM (Support Vector Machines) are better than Naïve Bayes’ for text categorization in theory, the classification precision of SVM is lower than Bayesian method in real world. This paper tries to find out the mysteries by analy...

Over a decade ago, Friedman et al. introduced the Tree Augmented Naïve Bayes (TAN) classifier, with experiments indicating that it significantly outperformed Naïve Bayes (NB) in terms of classification accuracy, whereas general Bayesian network (GBN) classifiers performed no better than NB. This paper challenges those claims, using a careful experimental analysis to show that GBN classifiers si...