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Medical decision-making can be a difficult task even for human experts. They can be helped by some automatic tools that are developed to offer suggestions when a decision has to be made. The system presented here uses artificial neural networks (ANN) in order to make predictions regarding the risk of Cerebrovascular Accident (CVA). The aim of this paper is to show that these intelligent (but artificial)...
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...
The article describes the automated informational and analytical system of a decision support in neural network diagnosis of diseases. The operation of the system is based on multi-level method of accounting management, analysis, generalization and exchange of experience between hierarchically organized geographically distributed medical centers. The Selecting of necessary settings for relearning...
In this article, the results of using neural network approach for solving hardly formalized task — diagnosing acute impairment of cerebral circulation, have been represented. Results of modeling neural network in the form of multilayer perceptron have been listed. The coefficients of diagnostic specificity, diagnostic sensitivity and diagnostic accuracy have been calculated.
This paper presents a system for classification of asthma based on artificial neural network. A total of 1800 Medical Reports were used for neural network training. The system was subsequently tested through the use of 1250 Medical Reports established by physicians from hospital Sarajevo. Out of the aforementioned Medical Reports, 728 were diagnoses of asthma, while 522 were healthy subjects. Out...
Machine learning algorithm and web-based application systems have played a major role in improving the healthcare organisation in terms of continuous tele-monitoring therapy and maintaining telemedicine management systems. Currently, no intelligent system has been used in terms of managing sickle cell disease. However, this paper presents a system that facilitates a shift from manual methods to automated...
Diagnosis of breast cancer disease depends on human experience. It is time consuming and has an element of human error in the results. This paper presents an intelligent multi-objective classifier to Diagnose breast cancer diseases using multilayer perceptron (MLP) neural network with Differential Evolution technique. The Differential Evolution (DE) algorithm is used to solve multi-objective optimization...
Medical diagnosis is done mostly by medical practitioner's expertise and experience. But in some cases, it may lead to wrong diagnosis and treatment. In this paper, a medical diagnosis system is proposed to predict the risk of cardiovascular diseases with high prediction accuracy. This system is built using an intelligent approach based on Principal Component Analysis (PCA) and Adaptive Neuro Fuzzy...
Prognostics and prediction of patients' short term physiological health status are of critical importance in medicine because they afford medical interventions that prevent escalating medical complications. This study proposes a prognostics engine to predict patient physiological status. The prognostics engine builds models from historical clinical data using neural network as its computational kernel...
In this research paper, the use of pattern recognition and data mining techniques into risk prediction models in the clinical domain of cardiovascular medicine is proposed. The data is to be modelled and classified by using classification data mining technique. Some of the limitations of the conventional medical scoring systems are that there is a presence of intrinsic linear combinations of variables...
Hybrid approach is a technique used with the combinations of basic technologies such as scientific standards based on statistical association, Bayesian networks, machine learning technique of neural network, fuzzy logic, genetic algorithms etc. While using it there can be certain strengths and weaknesses of the approach. The medical researchers and practitioners may use this approach for the prognosis...
In this study, we introduces a classification approach using Multi-Layer Perceptron (MLP)with Back-Propagation learning algorithm and a feature selection algorithm along with biomedical test values to diagnose heart disease. Clinical diagnosis is done mostly by doctor's expertise and experience. But still cases are reported of wrong diagnosis and treatment. Patients are asked to take number of tests...
The diagnosis of heart disease in most cases depends on a complex combination of clinical and pathological data. Because of this complexity, there exists a significant amount of interest among clinical professionals and researchers regarding the efficient and accurate prediction of heart disease. In this paper, we develop a heart disease predict system that can assist medical professionals in predicting...
To explore methods of establishing Clinical Diagnostic models of Idiopathic pulmonary fibrosis(IPF) syndromes in TCM (traditional Chinese medicine) by studying the results of data mining of IPF. The end fuzzy rule and result were get by the contrast of dynamic kohonen network and Decision Tree, their reliability was tested with the Fisher-iris data. The coincident diagnostic rate of dynamic kohonen...
Artificial Neural Network (ANN) are one of the recently explored advanced technologies which shows promise in the area of medical. In this paper, Radial Basis Function is used to predict the medical prescription of heart disease. This work includes the detailed information about the patient's symptoms and preprocessing was done. The trainee doctors can also use this web based tool for diagnosis and...
The classification of the sound heart into different valve-physiological heart disease categories is a complex pattern recognition task. This paper will purpose sound heart recognition for diagnosing heart disease with 4 type of Artificial Neural Network (ANN). We develop a simple model for the recognition of heart sounds, and demonstrate its utility in identifying features useful in diagnosis. We...
According to the complexity of collaborative medical diagnosis system, a model based on C-type neural is given. Based on the relation between C-type neural and fuzzy cognitive-map (FCM), how to compose many cognitive-maps(CM) and derive new CM is described. Because the system can integrate more knowledge from each agent both effect and side effect, the diagnosis error is minimized.
This paper proposes an artificial neural network (ANN) based approach to diagnose patients infected with hepatotropic virus and the stage of disease. The proposed method detects the disease and classifies its stage to be acute, chronic or cirrhosis. The input to the system is in the form of basic pathological data based on various liver function tests (LFTs) and specific virological markers. In addition,...
Classification of medical data is an important task in the prediction of any disease. It even helps doctors in their diagnosis decisions. Ensemble classifier is to generate a set of classifiers instead of one classifier for the classification of a new object, hoping that the combination of answers of multiple classification results in better performance. Tuberculosis (TB) is a disease caused by bacteria...
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