| Artificial intelligence (AI) |
Branch of computer science that develops machines to perform tasks that would usually require human intelligence |
| Machine learning (ML) |
Subfield of AI in which algorithms are trained to perform tasks by learning patterns from data rather than by explicit programming |
| Representation learning (RL) |
Subtype of ML in which algorithms learn the best features required to classify data on their own |
| Deep learning (DL) |
Type of RL in which algorithms learn a composition of features that reflect a hierarchy of structures in the data and provide detailed image classification output |
| Deep reinforcement learning (DRL) |
Technique combining DL and sequential learning to achieve a specific goal over several steps in a dynamic environment |
| Training dataset |
Dataset used to select the ideal parameters of a model after iterative adjustments |
| Validation dataset |
A (usually) distinct dataset used to test and adjust the parameters of a model |
| Neural networks |
Model of layers consisting of connected nodes broadly similar to neurons in a biological nervous system |
| Support vector machine (SVM) |
Classification technique that enables identification of an optimal separation plane between categories by receiving data inputs in a testing dataset and providing outputs that can be used in a separate validation dataset |
| Recurrent neural networks |
DL architecture for tasks involving sequential inputs such as speech or language and used for speech recognition and natural language processing and understanding (eg, predictive text suggestions for next words in a sequence) |
| Convolutional neural networks (CNN) |
DL architecture that adaptively learns hierarchies of features through back-propagation and is used for detection and recognition tasks in images (eg, face recognition) |
| Computer-aided detection/diagnosis |
Use of a computer algorithm to provide detection or a diagnosis of a specified object/region of interest |
| Transfer learning |
Ability of a trained CNN model to perform a separate task by using a relatively small dataset for the new task |
