Resumen

PATINO, Mariano Martinez; PEREZ, Ernesto Cortés  y  SANCHEZ, Sergio Sanchez. Early detection of breast cancer: classification of mammograms using a deep learning model. RISTI [online]. 2024, n.55, pp.21-37.  Epub 30-Sep-2024. ISSN 1646-9895.  https://doi.org/10.17013/risti.55.21-37.

Breast cancer is one of the main causes of death in women worldwide, reporting 47,832 deaths in Mexico alone between 2000 and 2010. For this reason, early detection through mammograms plays a fundamental role in its diagnosis and treatment. In this work, a deep learning neural network composed of 28 layers is presented to classify mammographic images of 500 x 500 pixels. The model includes convolution, batch normalization, ReLU activation and maxpooling layers, followed by fully connected layers and a softmax layer for multi-class classification. The proposed model achieved an accuracy of 99.3% in training and 99.4% in validation, showing superior performance to similar works.

Palabras clave : Breast cancer; deep learning; convolution; mammograms.

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