Figure 1.

Artificial intelligence and machine learning. While AI describes a programme capable of performing tasks typical of human intelligence, machine learning refers to the process through which an AI system is trained to learn. The two main types of machine learning used in medicine are supervised and unsupervised learning. In the former, different algorithms such as regression or more advanced methods reflecting the structure of the human brain (neural networks), using decision trees or projecting a data set into a higher-order space to identify optimal separation planes (hyperplanes in support vector machines) or combination thereof are used to predict the class or value of a given label. In unsupervised learning (e.g. clustering), the data set is analysed to identify inherent patterns of the data, often using hierarchical or k-means clustering methods.