Genetic Fuzzy System (GFS) based wavelet co-occurrence feature selection in mammogram classification for breast cancer diagnosis

American Cancer Society, 2015. http://www.cancer.org/Research/CancerFactsFigures/index. Beura, 2015, Mammogram classification using two dimensional discrete wavelet transform and gray-level co-occurrence matrix for detection of breast cancer, Neurocomputing, 154, 1, 10.1016/j.neucom.2014.12.032 Dhahbi, 2015, Breast cancer diagnosis in digitized mammograms using curvelet moments, Comp. Biol. Med., 64, 79, 10.1016/j.compbiomed.2015.06.012 Dheeba, 2014, Computer-aided detection of breast cancer on mammograms: a swarm intelligence optimized wavelet neural network approach, J. Biomed. Inf., 49, 45, 10.1016/j.jbi.2014.01.010 Eltoukhy, 2012, A statistical based feature extraction method for breast cancer diagnosis in digital mammogram using multiresolution representation, Computers in Biology and Medicine, 42, 123, 10.1016/j.compbiomed.2011.10.016 Pawar, 2006 Ramos, 2012, Texture extraction: an evaluation of ridgelet, wavelet and co-occurrence based methods applied to mammograms, Expert Syst. Appl., 39, 11036, 10.1016/j.eswa.2012.03.020 Vadive, 2013, A fuzzy rule-based approach for characterization of mammogram masses into BI-RADS shape categories, Comp. Biol. Med., 43, 259, 10.1016/j.compbiomed.2013.01.004