… With artificial intelligence programs that are trained on known or proven cases (“supervised”
learning [6]), a robust “source of truth” for each diagnosis is required and is always required …

… of what is meant by artificial intelligence and machine learning for the practicing … machine
learning might help solve them—perhaps bringing anesthesiology into an era of machine…

… artificial intelligence, data mining and machine learning as … artificial intelligence and machine
learning. PROBLEMS WITH ARTIFICIAL INTELLIGENCE (AI) AND MACHINE LEARNING (…

… Artificial intelligence, machine learning, and deep learning can be seen as matryoshkas
nested in each other. Artificial intelligence gathers … Machine learning is the dominant branch of …

… In this work, multivariate data analysis has been done using machine learning to detect
drivers’ … Finally, machine learning methods are used to detect and classify the driver state ie, …

… efficient artificial intelligence and machine-learning algorithms, … Analysis and learning from
publically available biomedical … , and health records by machine-learning architectures are …

… , and the relationship will be enriched by additional insights from machine learning. Machine
learning is useful because it allows important relationships between disparate pieces of …

… use of artificial intelligence and machine learning to augment … the roles of machine learning
and artificial intelligence in … of machine learning and artificial intelligence methods in drug …

… in artificial intelligence (AI) research has grown rapidly over the past few years, in part thanks
to the numerous successes of modern machine learning techniques such as deep learning…

… Artificial intelligence is a broad term referring to the application of computational algorithms
… AI is machine learning (ML). Machine learning is the process of building or learning statistical …