Use of Fuzzy Neural Network to Predict Coronary Heart Disease in a Malaysian Sample
نویسنده
چکیده
The purpose of this study was to evaluate the ability of fuzzy neural network model to predict the likelihood of coronary heart disease for individuals based on knowledge of their biomarkers, risk habits and demographic profiles. The prediction performance of fuzzy neural network models were measured in terms of percentage accuracies and compared with the prediction performance of logistic regression models. Provisionary results showed that four markers namely body mass index, systolic blood pressure, total cholesterol level, and age are the appropriate markers for the prediction of coronary heart disease in the sample studied. Fuzzy neural network models prediction performance were found to be superior to the logistic regression performance as well as to other results reported in related literature. Key-Words: coronary heart disease, fuzzy neural network, prediction performance.
منابع مشابه
Diagnosis of Coronary Artery Disease using Neuro-fuzzy-based Method
Background & Aim: Coronary artery disease is one of the most common diseases in different societies. Coronary angiography is established as one of the best methods for diagnosis of this disease. Angiography is an invasive and costly method. Furthermore, it is associated with risks such as death, heart attack, and stroke. Thus, this study introduces a neuro-fuzzy-based method which can help the ...
متن کاملUsing Combined Descriptive and Predictive Methods of Data Mining for Coronary Artery Disease Prediction: a Case Study Approach
Heart disease is one of the major causes of morbidity in the world. Currently, large proportions of healthcare data are not processed properly, thus, failing to be effectively used for decision making purposes. The risk of heart disease may be predicted via investigation of heart disease risk factors coupled with data mining knowledge. This paper presents a model developed using combined descri...
متن کاملComparison of Three Decision-Making Models in Differentiating Five Types of Heart Disease: A Case Study in Ghaem Sub-Specialty Hospital
Introduction: cardiovascular diseases are becoming the main cause of mortality and morbidity in most countries. This research goal was to predict the types of heart diseases for more accurate diagnosis by data mining and neural network technics. Method: This research was an applied-survey study and after data preprocessing, three approaches of neural network, decision making tree and Bayes simp...
متن کاملComparison of Three Decision-Making Models in Differentiating Five Types of Heart Disease: A Case Study in Ghaem Sub-Specialty Hospital
Introduction: cardiovascular diseases are becoming the main cause of mortality and morbidity in most countries. This research goal was to predict the types of heart diseases for more accurate diagnosis by data mining and neural network technics. Method: This research was an applied-survey study and after data preprocessing, three approaches of neural network, decision making tree and Bayes simp...
متن کاملThe use of wavelet - artificial neural network and adaptive neuro fuzzy inference system models to predict monthly precipitation
Precipitation forecasting due to its random nature in space and time always faced with many problems and this uncertainty reduces the validity of the forecasting model. Nowadays nonlinear networks as intelligent systems to predict such complex phenomena are widely used. One of the methods that have been considered in recent years in the fields of hydrology is use of wavelet transform as a moder...
متن کامل