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Session: Workshop - Medical Applications of Genetic and Evolutionary Computation Workshop (MedGEC) Title: Feature Selection for the Classification of Both Individual and Clustered Microcalcifications in Digital Mammograms Using Genetic Algorithms     Authors: Rolando R. Hernández-Cisneros Hugo Terashima-Marín     Abstract: Breast cancer is one of the main causes of death in women and early diagnosis is an important means to reduce the mortality rate. The presence of microcalcification clusters are primary indicators of early stages of malignant types of breast cancer and its detection is important to prevent the disease. This paper uses a procedure for the classification of microcalcification clusters in mammograms using sequential Difference of Gaussian filters (DoG) and a Genetic Algorithm (GA) for feature selection. We found that the use of Genetic Algorithms (GAs) for selecting the features from microcalcifications and microcalcification clusters that will be the inputs of a feedforward Neural Network (NN) results mainly in improvements in overall accuracy, sensitivity and specificity of the classification.