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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...
Lung sound is one of the important information in the diagnosis of respiratory disease. Many researchers have developed various algorithms to diagnose lung disease through the lung sounds. One of the parameters used as the feature of lung sound is entropy, a measure of the signal complexity in which the normal biological signal and the pathological biological signal have different complexities. Entropy...
Diagnosing liver disease is the challenging task for many public health physicians. In this study, we propose the framework to diagnose the hepatitis disease. For this study the adaptive rule based induction were formulated and the adaptive rule implemented in combined Robust BoxCox Transformation (RBCT) and Neural Network (NN) methods. The performance of proposed model is compared and results are...
In this paper, the various technologies of data mining (DM) models for forecast of heart disease are discussed. Data mining plays an important role in building an intelligent model for medical systems to detect heart disease (HD) using data sets of the patients, which involves risk factor associated with heart disease. Medical practitioners can help the patients by predicting the heart disease before...
Analysis of a medical dataset having missing values and then filling the missing values through different approaches exists in the literature. However, the classification accuracies achieved using these approaches have not been so promising when analyzed. It is this reason; which implicitly motivated us to study and address new methods for imputation. In this paper, we propose an approach for efficient...
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...
In biomedical engineering specifically in the branch of breathe analysis, the concentration of the gas in the breath is converted to a variation in resistance, such that each gas molecule is represented by a value of resistance. The array of resistive gas sensors analyze the gases released in breathe which are indications for many diseases. The resistance value is then converted to a current signal...
Genetic changes that may be associated with complex diseases are tried to be determined by means of many genome-wide association studies. Single Nucleotide Polymorphisms (SNPs) are used primarily in these studies since they comprise a large part of these genetic changes. Statistical importance of the genome-wide association study is directly related to the number of individuals and SNPs. However,...
Medical diagnosis is an exciting are of research and many researchers have been working on the application of Artificial Intelligence techniques to develop disease recognition systems. They are analysing currently available information and also biochemical data collecting from clinical laboratories and experts for identifying pathological status of the patient. During the process of diagnosis, the...
This paper presents a computational based system for detection and classification of lung nodules from chest CT scan images. In this study we consider the case of a primary lung cancer. Optimal thresholding and gray level characteristics are used for segmentation of lung nodules from the lung volume area. After detection of lung mass tissue, geometrical features are extracted. Simple image processing...
Pittsburgh compound B Positron Emission Tomography (PiB PET) imaging is a new technique to detect amyloid-beta (Aβ). Aβ is a pathological bio-data which appears distinctly in most neuro-degeneration diseases, such as Alzheimer's disease (AD). Although PiB PET imaging is relative mature, the accurate diagnosis of AD based on PiB PET images still remains a challenge for radiologists. To solve above...
In this paper, we focus on the need for a robust domain specific question answering system targeting agriculture domain. It aims to help farmers get information and resolve their queries related to agriculture and thereby improving agriculture literacy. The system is based on the principles of natural language processing and information retrieval. Most of the currently available information retrieval...
This paper proposes a Disease Inference Scheme based on Fuzzy Logic for Patient's-customized Healthcare. It consists of the Fuzzy-based Disease Rules Module (FDRM) and the Fuzzy-based Disease Inference Model (FDIM). The Fuzzy-based Disease Rules Module (FDRM) computes the conditional support between attributes and generates the Fuzzy Rules considering the relation between them, unlike the traditional...
Electrocardiogram (ECG) is a key diagnostic tool to visualize the heart's activity and to study its normal or abnormal functioning. Physicians perform routine diagnosis by visually examining the shapes of ECG waveform. However, automatic processing and classification of ECG data would be extremely useful in patient monitoring and telemedicine systems. Such realtime applications require techniques...
Air pollutants are really a hazardous problem in Bangladesh. This paper works on the relationship between the pollutants and the admittance of patients in the medical facilities and analyzes the reason behind the increase of the disease rate in the hospitals. The research collected medical data from the medical center named National Institute of Disease of the Chest and Hospital (NIDCH) that is located...
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...
Magnetocardiography is an advanced technique of measuring weak magnetic fields generated during heart functioning for diagnostics of huge number of different cardiovascular diseases. In this paper, k-nearest neighbor algorithm is applied for binary classification of myocardium current density distribution maps (CDDM). CDDMs from patients with negative T-peak, male and female patients with microvessels...
Blood vessel extraction from retinal fundus images is an important task in developing the computer-aided diagnostic system for ophthalmologists. In this paper we have presented an algorithm for extraction of blood vessels of retinal fundus images and comparison of different moment invariants used for the extraction of features for the vessel pixels. The algorithm uses neural networks for distinguishing...
As vertigo is common disease, it causes by problem with Nystagmus. It is difficult to diagnosis by observation. In this paper, we propose a method to detect nystagmus for vertigo diagnosis system using eye movement velocity. This method consists of three main steps: pupil extraction, velocity of eye movement computation, and nystagmus detection. An infrared camera is used to record eye movement in...
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