Machine learning: Machine learning is a specific branch of artificial intelligence, based on algorithms that enable computer systems to learn, make predictions, and decisions based on data, without the need for explicit programming instructions to do so.	Whole-slide images: Digital representations of entire microscope slides created by scanning glass slides with high-resolution scanners.
Deep learning: A subfield of machine learning where algorithms are trained for a task or set of tasks by subjecting a multi-layered artificial neural network to a training data. It eliminates the need for manual feature engineering by allowing the networks to learn directly from raw input data during the training process. The acquired algorithm is subsequently utilized for tasks such as classification, detection, or segmentation. The term "deep" refers to the use of artificial neural networks comprising numerous layers, thus referred to as deep neural networks.	Convolutional neural network: In deep learning, a class of artificial nural network consisting of convolutional of a sequence of convolutional layers to process an input data and produce an output. Each layer implements the convolution operation between the input data and a set of filters. These filter values are learned automatically during training, allowing the network to extract relevant features from the data in an end-to-end fashion (learning the optimal value of all parameters of the model simultaneously rather than sequentially)
Digital pathology: The process of digitizing the conventional diagnostic approach. It is accomplished through the utilization of whole-slide scanners and computer screens	Pathomics: The analysis by computational algorithms of digital pathology data, to extract meaningful features. These features are then used to build models for diagnostics, prognostics, and therapeutics purposes
Computational pathology: Computational analysis of digital images acquired by scanning pathology slides	Image segmentation: The process of dividing a digital pathology image into distinct regions or objects of interest (for example nuclei or tumor region) to enable analysis and extraction of specific features.