this paper is concerned with the development of a novel classifier for automatic mass detection of mammograms, based on contourlet feature extraction in conjunction with statistical and fuzzy classifiers. in this method, mammograms are segmented into regions of interest (roi) in order to extract features including geometrical and contourlet coefficients. the extracted features benefit from...

In this short note we analyze the performance of Backpropagation Neural Network (BPNN), Radial Basis Function Network (RBFN), Classification Based on Multiple Association Rule (CMAR) and Classification Based on Association (CBA) on mammographic mass data from UCI repository. The performance of the classifier is evaluated using sensitivity, specificity and classification accuracy.

High-dimensional classification has become an increasingly important problem. In this paper, we propose a “Multivariate Adaptive Stochastic Search” (MASS) approach which first reduces the dimension of the data space and then applies a standard classification method to the reduced space. One key advantage of MASS is that it automatically adjusts to mimic variable selection type methods, such as ...

Matrix assisted laser desorption ionization time of flight mass spectrometry has been explored as a tool to bacterial colony morphotyping. To this end, four colony morphotypes of Pseudomonas aeruginosa and four of Staphylococcus aureus were analysed using intact bacteria. Results suggest that mass spectrometry of intact bacteria could, in some extent, be used to complement the classical morphol...

Recent atmospheric neutrino data at Super-Kamiokande suggest the near-maximal flavor mixing. Models for the lepton mass matrix, which give the near-maximal flavor mixing, are discussed in this report. Mass matrix models are classified according to the mechanism providing the large flavor mixing, and those are reviewed briefly. " Naturalness " of the mass matrix is also discussed in order to sel...

Tandem mass spectrometry has emerged as a powerful tool for the characterization of complex protein samples, an increasingly important problem in biology. The effort to efficiently and accurately perform inference on data from tandem mass spectrometry experiments has resulted in several statistical methods. We use a common framework to describe the predominant methods and discuss them in detail...

High-dimensional classification has become an increasingly important problem. In this paper we propose a “Multivariate Adaptive Stochastic Search” (MASS) approach which first reduces the dimension of the data space and then applies a standard classification method to the reduced space. One key advantage of MASS is that it automatically adjusts to mimic variable selection type methods, such as t...