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This paper presents the development of a Neuro-genetic model for the prediction of coronary heart diseases. The novelty of this work is feature subset selection using multi-objective genetic algorithm without sacrificing the accuracy of ANN based heart disease predictor. Subsequently, the selected feature subset is used to predict the level of angiographic coronary heart disease using neural networks...
Disk hernia and spondylolisthesis are examples of pathologies on vertebral column. These traumas on vertebral column can affect spinal cord capability to send and receive messages from brain to the body systems that control sensor and motor. Therefore, accuracy and timeliness of diagnosis for these pathologies are critical. Hence, a classification system can assist radiologists to improve productivity...
Attention Deficit Hyperactivity Disorder (ADHD) is one of the common diseases of brain and has brought the growth of teenagers and even the adult indelible damage. It is very different to classify the ADHD symptoms and normal by the existing research. In this paper, the contributions are as two aspects: one is that the attributes of brain network of the resting state fMRI data have been calculated...
Recent survey shows that heart disease is a leading cause of death in India and in world wide. Significant life savings can be achieved, if a timely and cost effective clinical decision system is developed. Adverse reactions occur if a disease is not diagnosed properly. A clinical decision support system can assist health care professionals for early diagnosis of heart disease from patient's medical...
The paper presents a new way to apply text similarity computing to the Clinical Decision Support System. It can be applied to all kinds of diseases. Our method includes some traditional algorithms and their improvements, such as TF-IDF algorithm and Cosine Similarity algorithm. Besides, a new approach using TF-IDF algorithm combined eigenvector associated model to determine the case feature weights...
The aim of this study is to apply automatic speech recognition (ASR) mechanism to improve the amount of information extracted from the voice and to increase the accuracy of the system by using selective highly discriminative features among different types of acoustic features. For feature extraction, we applied three techniques which are Mel Frequency Cepstral Coefficient (MFCC), Linear Prediction...
At present, patients whose have suffered from stroke in Thailand are increasing every year. Stroke impairments relate to many functions such as sensory, motor function, communication, visual and emotional function which depend on brain's lesion. Physical examinations and assessments are important for planning the rehabilitation programs. For this reason, there are several information for medical decision...
An electric wheelchair is basically acknowledged for mobility improvement in disability patients. In some cases, their hand could not well function. They may tire easy before reaching to the desired destination. Furthermore, the safety is the most concerned issue for wheelchair control in disability patients. Therefore, this work tries to develop the prototype of the automated navigation system that...
MicroRNAs (MiRNA) are small non-coding RNAs that regulate gene expression. Up to date, seventy miRNAs have been found differentially expressed in lung whole tissue between smoking patients affected by Chronic Obstructive Pulmonary Disease (COPD) and smokers. The aim of this study was to explore the associated miRNAs with emphysema severity of COPD. Firstly, we identified miRNAs differentially expressed...
Large amount of medical data leads to the need of intelligent data mining tools in order to extract useful knowledge. Researchers have been using several statistical analysis and data mining techniques to improve the disease diagnosis accuracy in medical healthcare. Heart disease is considered as the leading cause of deaths worldwide over the past 10 years. Several researchers have introduced different...
According to the World Health Organization (WHO), as of 2012 esophageal cancer is the eighth-most common cancer globally with 456,000 new cases during the year. One of the triggers of the esophageal cancer is the hiatus hernia, and currently, the frequency disease increases with age, from 10% in patients younger than 40 years to 70% in patients older than 70 years old. Given the above, the aim of...
Protein sub network biomarkers for 144 diseases and pathways are analyzed in terms of protein-protein interaction (PPI) score available in STRING database. Most of the sub network biomarker (SNB) studies are to classify disease samples from the control. But no de novo algorithm is available to identify SNB from the whole genome PPI network without the knowledge of differentially expressed genes. Recently,...
There have been many studies that depict genotype-phenotype relationships by identifying genetic variants associated with a specific disease. Researchers focus more attention on interactions between SNPs that are strongly associated with disease in the absence of main effect. In this context, a number of machine learning and data mining tools are applied to identify the combinations of multi-locus...
Long non-coding RNAs (lncRNAs) have been implicated in various biological processes, and are linked in many dysregulations. Researchers have reported large number of lncRNA associated human diseases over the past decade. In this article we employed the Non-negative Matrix Factorization method to develop a low-dimensional computational model that can describe the existing knowledge about lncRNA-disease...
The prevalence of end-stage renal disease in the U.S. Has grown significantly, and continues to do so. Organ transplantation generally has better overall patient outcomes than dialysis. But there is a significant shortage of kidneys. This shortage is exacerbated by the need for kidneys for patients with dual organ transplantations. So the kidney allocation problem is a significant challenge. Predictive...
Various statistical and machine learning based algorithms have been proposed in literature for selecting an informative subset of genes from micro array data sets. The recent trend is to use functional knowledge to aid the gene selection process. In this paper we propose a clustering algorithm which generates multiple views (clusters) from the micro array expression profiles, each representing a particular...
Physical inactivity is an important contributor to non-communicable diseases in countries of high income, and increasingly so in those of low and middle income. Physical inactivity is the leading cause of many diseases. It has been estimated that as many as 250,000 deaths per year in the United States, approximately 12% of the total, are attributable to a lack of regular physical activity. Measuring...
The apparatus for vector electrocardiogram recording has developed. The principle of operation has been considered and technical characteristics of developed apparatus based on Frank's formulas are justified. The vector electrocardiogram recording procedure has been described. The way of electrocardiogram from vector electrocardiogram synthesis has been analyzed. Confidence limits of vector electrocardiogram...
Prevalence of communicable and non-communicable diseases is one of the most important categories of epidemiological data that is used for interpreting health status of communities. This study is aimed to calculate the prevalence of outpatient diseases through characterization of outpatient prescriptions. The data used in this study is collected from 1412 prescriptions of various diseases and we have...
Diagnosis of the disease is one of the application areas where data mining techniques helps in the extraction of knowledge from medical database. Recently, researchers have been investigating the effect of cascading more than one technique showing enhanced results in the diagnosis of the disease. This paper proposes a hybrid model using K-means as a preprocessing algorithm. The proposed model is developed...
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