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The aim of this study is to compare some classifiers' performance related to the tuples amount. The different metrics of performance has been considered, such as: Accuracy, Mean Absolute Error (MAE), and Kappa Statistic. In this research, the different numbers of tuples are considered as well. The readmission process dataset of Diabetic patients, which has been experimented, consists of 47 features...
The ubiquitous growth of Internet of Things (IoT) and its medical applications has improved the effectiveness in remote health monitoring systems of elderly people or patients who need long-term personal care. Nowadays, chronic illnesses, such as, stroke, heart disease, diabetes, cancer, chronic respiratory diseases are major causes of death, in many parts of the world. In this paper, we propose a...
This paper presents a new data-driven classification pipeline for discriminating two groups of individuals based on the medical images of their brain. The algorithm combines deformation-based morphometry and penalised linear discriminant analysis with resampling. The method is based on sparse representation of the original brain images using deformation logarithms reflecting the differences in the...
We have compared in Parkinson's diseases patients neurological data with the local cerebral blood flow measured by the Single-Photon Emission Computed Tomography. Most of our patients underwent Deep Brain Stimulation surgery or were qualified for one in relation to the advanced disease progression. Local cerebral blood flow in different areas has correlated to the Unified Parkinson's Disease Rating...
Data Mining is the process of discovering interesting patterns and knowledge from large amounts of data. One of the most important techniques of Data Mining is classification which is used for prediction purposes. In this paper, we present a novel classifier for classification in the field of Medical Data Mining. The idea is to apply the Adaptive Classifier on the sample medical dataset, and compare...
The diagnosis of the arythema disease is a real difficulty in dermatology. It causes redness induced in the lower level of the skin by hyperemia of the capillaries. It can harm several skin damages, inflammations. In this paper, we have put our efforts to design a diagnostic approach based on Support Vector Machine (SVM) with linear kernel by classifying the erythemato-squamous disease. SVM being...
Databases in clinical scenario have tremendous amount of data regarding patients and clinical history associated. Here, data mining plays vital role in searching for patterns within huge clinical data that could provide useful basis of knowledge for efficient and effective decision-making. Classification mechanism is widely used tool of data mining employed in healthcare applications to facilitate...
Asthma is a lung disease caused by the inflammation and narrowing of the airways that causes recurrent attacks of breathlessness and wheezing, and often can be life-threatening. Around 15–20 million people are suffering from asthma in India[1]. This paper aims at analyzing various data mining techniques for the prediction of asthma. The observations show that the fusion approach of naive bayes and...
Parkinson's disease (PD) is a chronic neurological progressive disorder caused by lack of the chemical dopamine in the brain. Up to today, there is still no cure or prevention for PD, and usually the disease worsens gradually over time. However, this disease can be controlled with some treatment, especially in the early stage. Hence, this study proposes a method in early detection and diagnosis of...
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...
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...
Chronic diseases are gradually becoming the principal factors of harm to people's health. Fortunately, the development of e-health provides a novel thought for chronic disease prevention and treatment. This paper focuses on the research of cardiovascular disease (CVDs) prevention and early warning techniques using e-health and data mining. In this paper, we will use weighted associative classification...
Primary tumor is a neoplasm which in clinical parlance is regarded as malignant, arising in one site and capable of giving rise to metastatic tumors. Primary tumor disease is a major health problem in today's time. This paper aims at analyzing various data mining techniques for primary tumor prediction. The observations reveal that the hybrid approach of any three classifiers using Vote ensemble technique...
In biomedical area, information is mainly in natural language text format. Such information is stored in huge repositories. It is not easy to access required information from this large amount of data. Also the classification systems developed for general text is not applicable for biomedical data. The biomedical researchers need fast and accurate information accessing tools for extracting useful...
In this study a new dataset are prepared for neuromuscular diseases using scanning EMG method and four new features are extracted. These features are maximum amplitude, phase duration at the maximum amplitude, maximum amplitude times phase duration, and number of peaks. By using statistical values such as mean and variance, number of features has increased up to eight. This dataset was classified...
Newcastle disease (ND) is one of the most serious infectious diseases of poultry, which have an important economic impact on poultry sector production. The causative agent of the disease is Newcastle disease virus (NDV). NDV strains can be classified into two types according to virulence, namely highly virulent (velogenic) and low virulent (lentogenic) based on their pathogenicity in chickens. In...
Heart disease is the most important reason of morbidity and mortality in the modern society. For that reason, it is important to have a proper diagnosis of heart disease for patients to live to tell the tale. In order to make the diagnosis system as the efficient one, heart diseases should be classified accurately. In the existing technique, the quality of the extracted rules is poor. So as to increase...
Feature selection is a vital process in classification of medical datasets. This paper addresses feature selection in Radial Basis Function (RBF) kernel space for the classification of multiclass dermatology dataset using neural network and data mining classifiers. It has three stages in determining relevant and irrelevant features for the classification task. In stage I, the features of dermatology...
In machine learning, selection of optimal features for the classifier is a critical problem. In order to address this problem a novel feature selection method named “Improved Normalized Point wise Mutual Information (INPMI)” is proposed. The proposed INPMI method coupled with Sequential forward search (SFS) finds the best feature subset to aid feature selection process. The key properties of evaluating...
Allergic rhinitis is a prevalent disease throughout the world. Electrodermal screening devices (EDSD) are devices that can measure the electrical properties of acupuncture points. This paper performs a series of experiments based on machine learning algorithms to study the feasibility of utilizing EDSD to diagnose allergic rhinitis. The experimental result shows that, to assess the presence of allergic...
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