# Artificial Intelligence in Ophthalmology: Advantages and Limits
## Appendix A Definitions and Acronyms of AI Terms
In pattern recognition, information retrieval, and classification (machine learning), recall (also known as sensitivity) is the fraction of relevant instances that were retrieved. **Recommendation system. ** A recommender system or a recommendation system (sometimes also called a recommendation platform or engine) is a subclass of information-filtering systems that seeks to predict the \"rating\" or \"preference\" a user would give to an item. **Recurrent Neural Networks (RNN). ** It is a neural network architecture commonly used in natural language processing and speech recognition, enabling previous outputs to be used as inputs for the current calculations. **Reinforcement learning. ** A type of machine learning in which a software program learns by interaction with its surroundings, being either rewarded or penalized based on its activity. **Responsible AI. ** A broad term that comprises the business and ethical choices related to how organizations use and develop AI capacities. Generally, Responsible AI seeks to enable Transparent (to see how an AI system works), Explainable (to explain why a specific decision in an AI system was taken), Fair (to ensure that a specific group is not discriminated based on an AI model's decision), and Sustainable (Can the development and curation of AI models be done on an environmentally sustainable basis?) use of AI. Sentiment analysis. Synonymous with opinion mining, sentiment analysis is the activity of analyzing the mood and opinion of a given text or video by means of AI. Sentiment is commonly measured on a linear scale (negative, neutral, or positive), but advanced implementations can categorize input data in terms of emotions, moods, and feelings. **Structured data. ** Defined and searchable data. It comprises different data, such as phone numbers, dates, or product stock-keeping units. **Supervised learning. ** A type of machine learning in which classified output data is used to train the algorithm, producing a correct software program. It is more usual than unsupervised learning. **SVM. ** Support Vector Machine (an ML method). **Token. ** A token is a basic unit of text that a Large Language Model uses to understand and generate language. A token may be a whole word or fragments of a word. **Training data. ** Training data comprise the information or samples offered to an AI application to allow it to learn, discover patterns, or generate new content. **Transfer learning. ** A machine learning method that uses previously learned data and applies it to new tasks and operations. **Unstructured data. ** Undefined and difficult-to-search data. This comprises audio, still images, and video content. Most existing data is unstructured. **Unsupervised learning. ** A type of machine learning in which a network is trained with unlabeled data in such a manner that it acts in the absence of supervision. **Validation data. ** Structured like training data with input and labels, this data is used to test a recently trained model against new data and to analyze performance, with a particular focus on checking for overfitting. **Voice recognition. ** Also known as speech recognition, it is a procedure of human-computer interaction in which computing programs listen to and interpret human speech and provide written or spoken outcomes. Examples include Apple's Siri and Amazon's Alexa, applications that allow hands-free requests and tasks. **Weak AI. ** Also called _narrow AI_, this is a model that has a set range of skills and focuses on one particular set of tasks. Most AI currently in use is weak AI, unable to learn or perform tasks outside of its specialized skill set.