Application of artificial intelligence in gastroenterology

Table 1 Artificial intelligence terminology

Artificial intelligence	Machine intelligence that has cognitive functions similar to those of humans such as “learning” and “problem solving.”
Machine learning	Mathematical algorithms which is automatically built from given data (known as input training data) and predicts or makes decisions in uncertain conditions without being explicitly programmed
Support vector machines	Discriminative classifier formally defined by an optimizing hyperplane with the largest functional margin
Artificial neural networks	Multilayered interconnected network which consists of an input, hidden connection (between the input and output layer), and output layer
Deep learning	Subset of machine learning technique that composed of multiple-layered neural network algorithms
Convolutional neural networks	Specific class of artificial neural networks that consists of (1) convolutional and pooling layers, which are the two main components to extract distinct features; and (2) fully connected layers to make an overall classification
Overfitting	Modelling error which occurs when a certain learning model tailors itself too much on the training dataset and predictions are not well generalized to new datasets
Spectrum bias	Systematic error occurs when the dataset used for model development does not adequately represent or reflect the range of patients who will be applied in clinical practice (target population)