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This study includes a classification structure consisting of first three stages for the automatic diagnosis of the neuromuscular disease of ALS (Amyotrophic Lateral Sclerosis) and myopathy being a muscular disease. In this study; EMG mark representing best MUAP will be determined for the right to comment sign EMG. After the first stage of the raw EMG data eliminated by noise the segmentation stage...
The disease Leukemia are continuously increasing among the people. The cause of leukemia is unknown but several factors, however are associated with the development of leukemia that are exposure to ionising radiation, exposure to benzene in rubber industry workers, cytotoxic drug particularly alkylating agent exposure, genetic disorder like down syndrome and immunological deficiency states. There...
Parkinson is a disease attacking the nervous system and worsens the work of nervous system over time. This disease is incurable, the therapy existing today is only able to help to relieve the symptoms. Hence, an early diagnose is deemed essential to determine an accurate type of therapy. Parkinson disease can be diagnosed by examining the symptoms apparent to the patient. One of the symptoms is the...
In the last two decades, several chaos-based cryptosystems have been proposed. Some of them have architecture comprising a layer of permutation and a layer of diffusion and these layers are simultaneously executed in a simple scan of plain-image pixels. In this kind of cryptosystems, due to the channel effect, a bit error(s) in the cipher-image produces, at the decryption side, a random bit error...
Alzheimer's disease (AD) is one major cause of dementia. Previous studies have indicated that the use of features derived from Positron Emission Tomography (PET) scans lead to more accurate and earlier diagnosis of AD, compared to the traditional approach used for determining dementia ratings, which uses a combination of clinical assessments such as memory tests. In this study, we compare Naïve Bayes...
Gene Selection is very important problem in the classification of serious diseases in clinical information systems. A limitation of these gene selection methods is that they may result in gene sets with some redundancy and yield an unnecessary large number of candidate genes for classification analysis. In the current work, a hybrid approach is presented in order to classify diseases, such as colon...
With the rapid development of high-throughput genotyping technologies, more and more attentions are paid to the disease association study identifying DNA variations that are highly associated with a specific disease. One main challenge for this study is to find the optimal subsets of Single Nucleotide Polymorphisms (SNPs) which are most tightly associated with diseases. Feature selection which might...
The Primary Open Angle Glaucoma(POAG) discriminated model using support vector machine(SVC) method is presented to distinguish the primary open-angle glaucoma disease, which is not clear in early symptoms and involves in various risk factors, moreover easy to blind with prolonged intraocular hypertension. Through case study of clinical diagnosis, SVM classifier with a radial basis inner function was...
There have been a lot of researches that demonstrate the phenomenon of life or the origin of the disease and classify or diagnose the state of the cell. These are usually achieved by the strength of the gene expression under certain circumstances by the microarray which can observe tens and thousands of gene expression profile. It is not feasible to use all the attributes because a lots of gene expression...
It is widely accepted and can be easily verified that any specific voxel in a class of brain single photon emission computed tomography (SPECT) volumes is of a univariate normal distribution. In this research, we conjecture that all the voxels in a class of SPECT volumes are also approximately of a multivariate normal (MVN) distribution from which in terms of the Bayes errors of statistics, an optimal...
In recent years Microelectrode recording (MER) analysis has proved to be a powerful localization tool of basal ganglia for Parkinson disease's treatment, especially the Subthalamic Nucleus (STN). In this paper, a signal-dependent method is presented for identification of the STN and other brain zones in Parkinsonian patients. The proposed method, refereed as optimal wavelet feature extraction method...
Clinical databases have accumulated large quantities of information about patients and their clinical history. Data mining is the search for relationships and patterns within this data that could provide useful knowledge for effective decision-making. Classification analysis is one of the widely adopted data mining techniques for healthcare applications to support medical diagnosis, improving quality...
Various techniques have been developed for texture classification which can be used for an automated classification of endoscopic images. A certain subset of these techniques is applied to duodenal imagery for diagnosis of celiac disease. Spatial domain (histogram) and transform domain (wavelet) features are extracted from the images for subsequent classification with various algorithms (KNN, SVM,...
The tongue diagnosis is an important diagnostic method in traditional chinese medicine (TCM). In this paper, we present a novel computerized tongue inspection method based on support vector machine (SVM). First, two kinds of quantitative features, chromatic and textural measures, are extracted from tongue images by using popular image processing techniques. Then, support vector machine and Bayesian...
Human heart failure is a complex syndrome that can be initiated by a variety of clinical conditions and genetic factors. Gene expression profiling offers opportunities to study changes in transcriptional activity in heart failure samples of different etiologies. This paper evaluates machine and statistical learning models for supporting the identification of heart failure etiology based on gene expression...
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