Efficient heart disease prediction-based on optimal feature selection using DFCSS and classification by improved Elman-SFO - Wankhede, Jaishri; Kumar, Magesh; Sambandam, Palaniappan (IET systems biology, 2020)
Keywords: Algorithms; Bayes methods; California Irvine Cleveland heart disease dataset; cardiology; cardiovascular disease; cardiovascular system; clinical data analysis; Computer Simulation; CVD dataset; data analysis; data classification; data cleaning; data handling; data mining; data normalisation; data pre‐processing process; data transformation; decision function‐based chaotic salp swarm algorithm; decision trees; DFCSS–IENN‐based SFO algorithm; DFCSS–IESFO; diseases; efficient heart disease prediction‐based; feature extraction; feature selection; feature selection process; Heart Diseases - classification; high‐classification accuracy; Humans; improved Elman neural network; improved Elman‐SFO; learning (artificial intelligence); medical diagnostic computing; neural nets; Neural Networks, Computer; optimal feature selection; optimal features; optimal weight value; pattern classification; regression analysis; Research Article; sailfish optimisation algorithm; support vector machines; values imputation; data mining; regression analysis; California Irvine Cleveland heart disease dataset; feature extraction; efficient heart disease prediction-based; data classification; CVD dataset; clinical data analysis; DFCSS–IENN-based SFO algorithm; data transformation; learning (artificial intelligence); feature selection; optimal weight value; medical diagnostic computing; improved Elman neural network; pattern classification; cardiovascular disease; cardiovascular system; support vector machines; data analysis; optimal features; DFCSS–IESFO; diseases; data normalisation; data pre-processing process; cardiology; high-classification accuracy; feature selection process; improved Elman-SFO; data cleaning; decision trees; sailfish optimisation algorithm; decision function-based chaotic salp swarm algorithm; Bayes methods; data handling; optimal feature selection; values imputation; neural nets