introduction: amajor problem in the treatment of cancer is the lack of an appropriate method for the early diagnosis of the disease. the chemical reaction within an organ may be reflected in the form of proteomic patterns in the serum, sputum, or urine. laser mass spectrometry is a valuable tool for extracting the proteomic patterns from biological samples. a major challenge in extracting such ...

Introduction: Application of biofeedback techniques in rehabilitation has turned into an exciting research area during the recent decade. Providing an appropriate visual or auditory biofeedback signal is the most critical requirement of a biofeedback technique. In this regard, changes in Surface Electromyography (SEMG) signals during wrist movement can be used to generate an indictable visual b...

Purpose: To assess three main emotions (happy, sad and calm) by various classifiers, using appropriate feature extraction and feature selection. Materials and Methods: In this study a combination of Power Spectral Density and a series of statistical features are proposed as statistical-frequency features. Next, a feature selection method from pattern recognition (PR) Tools is presented to e...

background: numerous studies used microarray gene expression data to extract metastasis-driving gene signatures for the prediction of breast cancer relapse. however, the accuracy and generality of the previously introduced biomarkers are not acceptable for reliable usage in independent datasets. this inadequacy is attributed to ignoring gene interactions by simple feature selection methods, due...

Steel consumption is a critical factor affecting pricing decisions and a key element to achieve sustainable industrial development. Forecasting future trends of steel consumption based on analysis of nonlinear patterns using artificial intelligence (AI) techniques is the main purpose of this paper. Because there are several features affecting target variable which make the analysis of relations...

purpose: to assess three main emotions (happy, sad and calm) by various classifiers, using appropriate feature extraction and feature selection. materials and methods: in this study a combination of power spectral density and a series of statistical features are proposed as statistical-frequency features. next, a feature selection method from pattern recognition (pr) tools is presented to extra...

Data dimensionality is growing exponentially, which poses challenges to the vast majority of existing mining and learning algorithms, such as the curse of dimensionality, large storage requirement, and high computational cost. Feature selection has been proven to be an effective and efficient way to prepare high dimensional data for data mining and machine learning. The recent emergence of nove...

Many scientific disciplines use modelling and simulation processes and techniques in order to implement non-linear mapping between the input and the output variables for a given system under study. Any variable that helps to solve the problem may be considered as input. Ideally, any classifier or regressor should be able to detect important features and discard irrelevant features, and conseque...