Enhanced Evolutionary Feature Selection and Ensemble Method for Cardiovascular Disease Prediction

[1] Antoniadis A(2003)Effective dimension reduction methods for tumor classification using gene expression data Bioinformatics 19 563-570

[2] Lambert-Lacroix S(2002)Gene selection for cancer classification using support vector machines Mach Learn 46 389-422

[3] Leblanc F(2005)Ovarian cancer identification based on dimensionality reduction for high-throughput mass spectrometry data Bioinformatics 21 2200-2209

[4] Guyon I(2004)Hybrid genetic algorithms for feature selection IEEE Trans Pattern Anal Mach Intell 26 1424-1437

[5] Weston J(2019)A review of feature selection methods in medical applications Comput Biol Med 112 103375-189

[6] Barnhill S(2018)Feature selection and classification systems for chronic disease prediction: a review Egyptian Inform J 19 179-260

[7] Vapnik V(2015)Machine learning: trends, perspectives, and prospects Science 349 255-30

[8] Yu JS(2012)Applying machine learning methods in diagnosing heart disease for diabetic patients Int J Appl Inf Syst 3 25-8630

[9] Ongarello S(2009)A hybrid evolutionary algorithm for attribute selection in data mining Expert Syst Appl 36 8616-343

[10] Fiedler R(2006)Association rule discovery with the train and test approach for heart disease prediction IEEE Trans Inf Technol Biomed 10 334-104

[1] Antoniadis A(2003)Effective dimension reduction methods for tumor classification using gene expression data Bioinformatics 19 563-570

[2] Lambert-Lacroix S(2002)Gene selection for cancer classification using support vector machines Mach Learn 46 389-422

[3] Leblanc F(2005)Ovarian cancer identification based on dimensionality reduction for high-throughput mass spectrometry data Bioinformatics 21 2200-2209

[4] Guyon I(2004)Hybrid genetic algorithms for feature selection IEEE Trans Pattern Anal Mach Intell 26 1424-1437

[5] Weston J(2019)A review of feature selection methods in medical applications Comput Biol Med 112 103375-189

[6] Barnhill S(2018)Feature selection and classification systems for chronic disease prediction: a review Egyptian Inform J 19 179-260

[7] Vapnik V(2015)Machine learning: trends, perspectives, and prospects Science 349 255-30

[8] Yu JS(2012)Applying machine learning methods in diagnosing heart disease for diabetic patients Int J Appl Inf Syst 3 25-8630

[9] Ongarello S(2009)A hybrid evolutionary algorithm for attribute selection in data mining Expert Syst Appl 36 8616-343

[10] Fiedler R(2006)Association rule discovery with the train and test approach for heart disease prediction IEEE Trans Inf Technol Biomed 10 334-104