**9. Deep learning**

Attempts to mimic the functioning of the human nervous system, using what is known as neural networks or layers of the processing unit (artificial neurons) that specialize in identifying characteristics or patterns determined in objects or unstructured data sets, without the need for prior training with a set of structured or labeled data. Neural networks: in Neurology, clinical applications of neural networks in sleep apnea-hypopnea syndrome were recognized, and *backpropagation* (BP) algorithms were also programmed. The BP algorithm is used to train the feed-forward neural network for human activity recognition in intelligent home environments in conjunction with probabilistic algorithms: the Naïve Bayes (NB) classifier and the Hidden Markov Model (HMM), neural networks for diabetes control using a multipanel graphic interface, neurological disease estimation [31, 33].
