Book ChapterDOI
Risk Prediction of Heart Disease Based on Swarm Optimized Neural Network
R. Chitra,V. Seenivasagam +1 more
- pp 707-714
TLDR
Multi-layer feedforward neural network optimized with particle swarm optimization (PSO) is adopted for HD prediction at the early stage using the patient’s medical record and the results show the proposed system can predict the likelihood of HD patients in a more efficient and accurate way.Abstract:
Heart disease (HD) remains the biggest cause of deaths worldwide. This shows the importance of HD prediction at the early stage. In this paper, multi-layer feedforward neural network (MLFFNN) optimized with particle swarm optimization (PSO) is adopted for HD prediction at the early stage using the patient’s medical record. The network parameters considered for optimization are the number of hidden neurons, momentum factor, and learning rate. The efficiency of the PSO optimized neural network (PSONN) is calculated using the records collected from standard Cleveland database and Real time clinical dataset. The results show the proposed system can predict the likelihood of HD patients in a more efficient and accurate way.read more
Citations
More filters
Journal ArticleDOI
A hybrid recurrent neural network-logistic chaos-based whale optimization framework for heart disease prediction with electronic health records
TL;DR: A novel hybrid recurrent neural network (RNN)‐logistic chaos‐based whale optimization (LCBWO) structured hybrid framework for predicting heart disease within 5 years using EHR data is proposed and achieves a higher accuracy of 98%, a specificity of 99, precision of 96, and a prediction time of 9.23 seconds.
Journal ArticleDOI
A New Hybrid Intelligent System for Prediction of Medical Diseases
TL;DR: The significance tests results have proven that the proposed algorithm is effective to solve neural networks with good generalization ability and network structure for medical diseases detection.
Proceedings ArticleDOI
A survey on Intelligent Data Mining Techniques used in Heart Disease Prediction
TL;DR: It is revealed from this survey, even though usage of one data mining technique performs well, hybrid data mining techniques yield promising outcomes in the determination of coronary illness.
References
More filters
Proceedings ArticleDOI
Particle swarm optimization
TL;DR: A concept for the optimization of nonlinear functions using particle swarm methodology is introduced, and the evolution of several paradigms is outlined, and an implementation of one of the paradigm is discussed.
Proceedings ArticleDOI
Intelligent heart disease prediction system using data mining techniques
Sellappan Palaniappan,R. Awang +1 more
TL;DR: This research has developed a prototype Intelligent Heart Disease Prediction System (IHDPS) using data mining techniques, namely, Decision Trees, Naive Bayes and Neural Network, which shows that each technique has its unique strength in realizing the objectives of the defined mining goals.
Applications of Data Mining Techniques in Healthcare and Prediction of Heart Attacks
TL;DR: The potential use of classification based data mining techniques such as Rule based, Decision tree, Naive Bayes and Artificial Neural Network to massive volume of healthcare data is examined.
Journal ArticleDOI
Towards designing artificial neural networks by evolution
TL;DR: This paper describes an evolutionary programming (EP) based system to evolve both architectures and connection weights (including biases) of ANNs and gives some of the experimental results which show the effectiveness of the system.
Journal ArticleDOI
Application of Genetic Algorithm Optimized Neural Network Connection Weights for Medical Diagnosis of PIMA Indians Diabetes
TL;DR: This paper presents the application of hybrid model that integrates Genetic Algorithm and Back Propatation network (BPN) where GA is used to initialize and optmize the connection weights of BPN .