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Artificial intelligence (AI), in its broadest sense, is intelligence exhibited by machines, particularly computer systems.It is a field of research in computer science that develops and studies methods and software that enable machines to perceive their environment and use learning and intelligence to take actions that maximize their chances of achieving defined goals. [1]
Explainable AI (XAI), often overlapping with interpretable AI, or explainable machine learning (XML), is a field of research within artificial intelligence (AI) that explores methods that provide humans with the ability of intellectual oversight over AI algorithms.
Subsymbolic methods emphasize prediction over explanation, and yield models which works well but are difficult or impossible to explain which has earned them the name black box AI. A black-box model cannot be considered a scientific hypothesis, and this development has even led some researchers to suggest that the traditional aim of science ...
Sep. 16—An 18-month study on the potential effectiveness of an artificial intelligence (AI) tool in the detection of cognitive impairment demonstrated the effectiveness of AI tools in detecting ...
To make the data amenable for machine learning, an expert may have to apply appropriate data pre-processing, feature engineering, feature extraction, and feature selection methods. After these steps, practitioners must then perform algorithm selection and hyperparameter optimization to maximize the predictive performance of their model.
Study to examine EEG correlates of genetic predisposition to alcoholism. Measurements from 64 electrodes placed on the scalp sampled at 256 Hz (3.9 ms epoch) for 1 second. 122 Text Classification 1999 [262] H. Begleiter P300 Interface Dataset Data from nine subjects collected using P300-based brain-computer interface for disabled subjects.
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