One of the most invasive cancer types which affect women is breast cancer. Unfortunately, it exhibits a high mortality
rate. Automated histopathological image analysis can help to diagnose the disease. Therefore, computer aided diagnosis by
intelligent image analysis can help in the diagnosis tasks associated with this disease. Here we propose an automated system for
histopathological image analysis that is based on deep learning neural networks with convolutional layers. Rather than a single
network, an ensemble of them is built so as to attain higher recognition rates, which are obtained by computing a consensus
decision from the individual networks of the ensemble. A final step involves the optimization of the set of networks that are
included in the ensemble by a genetic algorithm. Experimental results are provided with a set of benchmark images, with
favorable outcomes.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech
