The abnormal functioning of hormones produces the appearance of malformations in human bodies that must be detected early. In this manuscript, two proposals are presented for the identification of thyroid nodules in ultrasound images, using convolutional neural networks. For the network training, 400 images obtained from a medical center and stored in a database have been used. Free access software (Python and TensorFlow) has been used as part of the algorithm development, following the stages of image preprocessing, network training, filtering and layer construction. Results graphically present the incidence of people suffering from this health problem. In addition, based on the respective tests, it is identified that the system developed in Python has greater precision and accuracy, 90% and 81% respectively, than TensorFlow design. Through neural networks, the recognition up to 4 mm thyroid nodules is evidenced.