Table 1.

Glossary of Common Terms and Definitions Used in Artificial Intelligence Domains.

Artificial intelligence (AI)	A mathematical process of computer mediating designing of algorithms and models to augment, recreate and support the natural human intelligence and decision-making. AI lets machines perform tasks that would normally require human intelligence.
Algorithms	Collection of specific mathematical formulae that would form the basis of a computational learning methodology.
Data	Data is a conglomerate of information used for processing, which can be in the form of numbers, alphabets, images or videos.
Machine learning (ML)	Type of learning through computer-based predictions using mathematical algorithm by analysis of provided data. It helps in predictions about unseen data using learned data.
Deep learning (DL)	Advanced and complex form of machine learning that uses multiple algorithms arranged in complex neural networks. Due to interweaving of multiple algorithms, infinite patterns and complex data can be generated from data sets.
Artificial or Convolutional neural network (ANN/CNN)	Neural networks are complex models generated by arranging together algorithms in layers. The most superficial layer draws out the most readily accessible data, analyses it, and then triggers selected deeper layers. Deeper layers in turn extract finer data and then trigger even deeper layers. Once the deepest layer is triggered, the complex neural network will make a prediction.
Training dataset	Data sets that are used for initial development of complex algorithms. This data is analysed again and again in a repetitive fashion until output is generated that matches the reference label.
Validation dataset	Data sets used to fine-tune algorithms and adjust the parameters of a model.
Supervised learning	Refers to use of labelled data to train algorithms. Once trained, the algorithm can be used to generate labels for new, unseen data. Most commonly used in medical research for AI tools.
Unsupervised learning	Refers to use of unlabelled data to train algorithms. Complex method and not used widely for medical applications.

Abbreviations: AI, artificial intelligence; ANN, artificial neural network; CNN, convolutional neural network; DL, deep learning; ML, machine learning.