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Artificial intelligence in healthcare is the application of artificial intelligence (AI) to analyze and understand complex medical and healthcare data. In some cases, it can exceed or augment human capabilities by providing better or faster ways to diagnose, treat, or prevent disease.
National Survey on Drug Use and Health Large scale survey on health and drug use in the United States. None. 55,268 Text Classification, regression 2012 [269] United States Department of Health and Human Services: Lung Cancer Dataset Lung cancer dataset without attribute definitions 56 features are given for each case 32 Text Classification 1992
A pioneer in the use of artificial intelligence in healthcare was American biomedical informatician Edward H. Shortliffe. This field deals with utilization of machine-learning algorithms and artificial intelligence, to emulate human cognition in the analysis, interpretation, and comprehension of complicated medical and healthcare data.
Open-source artificial intelligence is an AI system that is freely available to use, study, modify, and share. [1] These attributes extend to each of the system's components, including datasets, code, and model parameters, promoting a collaborative and transparent approach to AI development. [1]
Advanced artificial intelligence systems have the potential to create extreme new risks, such as fueling widespread job losses, enabling terrorism or running amok, experts said in a first-of-its ...
This makes it possible to confirm existing knowledge, challenge existing knowledge, and generate new assumptions. [12] Machine learning (ML) algorithms used in AI can be categorized as white-box or black-box. [13] White-box models provide results that are understandable to experts in the domain.
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