sleep stages classification is one of the most important methods for diagnosis in psychiatry and neurology. in this paper, a combination of three kinds of classifiers are proposed which classify the eeg signal into five sleep stages including awake, n-rem (non-rapid eye movement) stage 1, n-rem stage 2, n-rem stage 3 and 4 (also called slow wave sleep), and rem. twenty-five all night recordings...

Objective(s): This study addresses feature selection for breast cancer diagnosis. The present process uses a wrapper approach using GA-based on feature selection and PS-classifier. The results of experiment show that the proposed model is comparable to the other models on Wisconsin breast cancer datasets. Materials and Methods: To evaluate effectiveness of proposed feature selection method, we ...

Basically, medical diagnosis problems are the most effective component of treatment policies. Recently, significant advances have been formed in medical diagnosis fields using data mining techniques. Data mining or Knowledge Discovery is searching large databases to discover patterns and evaluate the probability of next occurrences. In this paper, Bayesian Classifier is used as a Non-linear dat...

conclusions by comparing the results of classification using multiple classifier fusion with respect to using each classifier separately, it is found that the classifier fusion is more effective in enhancing the detection accuracy. objectives through the improvement of classification accuracy rate, this work aims to present a computer-assisted diagnosis system for malaria parasite. materials an...

This paper shows that some time series problems can be better served as non-time series problems. We used two unsupervised learning anomaly detectors to analyse a vehicle related time series problem and showed that non-time series treatment produced a better outcome than a time series treatment. We also present the benefits of using unsupervised methods over semisupervised or supervised learnin...

Communities of autonomous units are being developed for formal specification and semantic analysis of systems of interacting and mobile components. The autonomous units of a community are rulebased, self-controlled, goal-driven, and operate and move in a common environment. We employ communities of autonomous units to model the dynamic pickup and delivery problem with the general idea to demons...

There has been much recent interest in the extraction of PPIs (protein-protein interactions) from biomedical texts, but in order to assist with curation efforts, the PPIs must be enriched with further information of biological interest. This paper describes the implementation of a system to extract and enrich PPIs, developed and tested using an annotated corpus of biomedical texts, and employin...

Developing constraint solvers which are key requisites of constraint programming languages is time consuming and difficult. In this paper, we propose a generic algorithm that symbolically constructs rulebased solvers from the intensional definition of the constraint. Unlike the well-established “generate and test” approach, our symbolic construction approach is capable of generating recursive r...