9 A convolutional neural network (CNN) is a type of ANN that processes data with grid-like structures (such as images). 8 Deep learning is a subset of ANNs where at least 3 layers are used in the network. The output of a layer becomes the input for the next layer, until it has been transformed into an output that can be used by the network. ANNs use layers of processing to make sense of input information. 7 An artificial neural network (ANN) utilizes components of supervised and reinforcement learning to solve problems. 5 Reinforcement learning is the training of a ML model to make a sequence of decisions to solve a task through a process of trial and error. 5 Unsupervised learning algorithms find patterns (eg, in cluster analysis) in unlabeled datasets. 6 Supervised learning requires labelled datapoints for a ML algorithm to learn from, to later make predictions on unlabeled data. 5 ML algorithms can be split into 3 main categories: supervised learning, unsupervised learning, and reinforcement learning. Machine learning (ML) is a subset of AI that uses prior data to make improved decisions about future data.

In this field there are several definitions that should be considered ( Figure 1).

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