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Data mining technique in the history of medical data found with enormous investigations found that the prediction of heart disease is very important in medical science. In medical history it is observed that the unstructured data as heterogeneous data and it is observed that the data formed with different attributes should be analyzed to predict and provide information for making diagnosis of a heart...
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...
Glaucoma is a silent thief of sight. Detecting glaucoma at early stages is almost impossible and presently there is no cure of glaucoma at later stages. Different automated glaucoma detection systems were thoroughly analyzed in this study. A detailed literature survey of preprocessing, feature extraction, feature selection, Machine Learning (ML) techniques and data sets used for testing and training...
Plant disease management is an important factor in agriculture as it causes a significant yield loss in crops. Late Blight is the most devastating disease for Potato in most of the potato growing regions in the world. For optimum use of pesticide and to minimize the yield loss, the identification of disease severity is essential. The key contribution here is an algorithm to determine the severity...
Diagnosis of the thyroid function abnormalities may take much precious time of the patient. So, a computer aided diagnosis system can guide physicians in diagnosis and can save time of the patient. In this study, seven different types of neural networks were implemented in order to realize more robust and reliable networks on thyroid diagnosis. The particle swarm optimization and artificial bee colony...
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...
In this paper, a novel method for detecting the onset of Alzheimer's disease (AD) from Magnetic Resonance Imaging (MRI) scans is presented. It uses a combination of three different machine learning algorithms in order to get improved results and is based on a three-class classification problem. The three classes for classification considered in this study are normal, very mild AD and mild and moderate...
An artificial intelligence system has been developed using Artificial Neural Networks (ANN) algorithms to diagnose heart disease from Phonocardiogram (PCG) signals. Four new featured characteristics of the signals, namely activity, complexity, mobility and the spectral peaks from the power spectral density plots are used as input to the neural network. Ninety-four PCG signals for three heart diseases...
Digital image recognition of plant diseases could reduce the dependence of agricultural production on the professional and technical personnel in plant protection field and is conducive to the development of plant protection informatization. In order to find out a method to realize image recognition of plant diseases, four kinds of neural networks including backpropagation (BP) networks, radial basis...
The skill of cardiac auscultatory is very important to physicians for accurate diagnosis of many heart diseases. However, it needs some training and experience to improve the skills of medical students in recognizing and distinguishing the primary symptoms of cardiac diseases based on the heart sound that heard. This paper presents a method for feature extraction and classification of heart sound...
Artificial intelligence is used to predict the onset of diabetes based on data measured from Pima Indians. This research is comparing the results gained from using same artificial neural networks-back propagation (ANN-BP) engine for 2 differently prepared data. The first data set consists of the entire data set which is cross validated, while the second dataset is segregated into 2 groups using Kohonen...
Cancer is a group of complex diseases, in which a relatively large number of genes are involved. One of the main goals of cancer research is to identify genes that causally relevant to the development and progress of cancer. The increasingly identified cancer genes and availability of genomic and proteomics data provide us opportunities to identify cancer genes by computational methods. In this work,...
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