Table 3.

Most used algorithms of deep learning in medical research.

Algorithm	Brief Description
Multilayer perceptron (MLP)	Multiple layers system with a basic unit (perceptron). It allows a forward-directed flow of data from the input layer to the output one, passing through the hidden layer/layers, and with a learning algorithm of backward propagation.
Deep Learning	It provides a dissection of various levels that correlate to peculiar levels of abstraction.
Convolutional Neural Networks (CNNs)	An MLP development applied to two-dimensional matrices through a convolution operation. CNN neurons are linked to a limited number of inputs of a confined continuous region, used for computer vision tasks.
Recurrent neural networks (RNNs)	Uses sequential data or time-series data and develops loops between layers, storing memories for a short time. They are used for voice recognition.
Deep belief networks (DBNs)	Links between layers but not between elements within the same layer.
Long short-term memory (LSTM)	Advanced version of RNN that stores information for a more extended period (“long-term dependencies”).
Mixed Networks	Hybrid networks built by the correlation of two or more particular ANNs (e.g., CNNs and RNNs).