Modelo Machine Learning para la detección de tumores cerebrales mediante un conjunto de imágenes de resonancias magnéticas.

Abstract

Machine Learning is used in some fields of knowledge, such as medicine, for its prediction of the effectiveness of disease treatments and decision making after the identification of patterns. This allows the creation of support tools for diagnosis, such as the ML Model for the detection of brain tumors through magnetic resonance imaging that is proposed, which will allow the automation of this process, to speed up the diagnosis of the treating physician. We learned about neural networks, transfer learning, ResNet 50 architecture, Deep Learning, and convolutional neural networks. A descriptive methodology with qualitative approach and interviews with medical professionals was used, in addition to evolutionary prototyping as a development methodology. It was learned that technology has relevance in medicine, and that it is convenient to implement a tool to support decision making in the diagnosis of brain tumors. From the evaluation of the prototype, an acceptable success rate for the development of the tool was obtained. At the end, some conclusions and recommendations to be considered for possible future work were proposed.