artificial intelligence

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ar·ti·fi·cial in·tel·li·gence

1. a branch of computer science in which attempts are made to replicate human intellectual functions. One application is the development of computer programs for diagnosis. Such programs are often based on epidemiologic analysis of data in large numbers of medical records;
2. a machine that replicates human intellectual functions, although no machine (that is, computer) can do this yet.
Farlex Partner Medical Dictionary © Farlex 2012

artificial intelligence

Informatics The study of intelligence using ideas and methods of computation whose central goal is to understand the principles that make intelligence possible; a format of computer programming that attempts to simulate human 'intelligence.' See Bayesian network, Expert system, Machine learning, Neural networking, Symbolic reasoning.
McGraw-Hill Concise Dictionary of Modern Medicine. © 2002 by The McGraw-Hill Companies, Inc.

ar·ti·fi·cial in·tel·li·gence

(AI) (ahr-ti-fishăl in-teli-jĕns)
Branch of computer science in which attempts are made to replicate human intellectual functions. One application is the development of computer programs for diagnosis. Such programs are often based on epidemiologic analysis of data in large numbers of medical records.
Medical Dictionary for the Health Professions and Nursing © Farlex 2012

artificial intelligence

The characteristics of a machine designed to perform some of the perceptive or logical functions of the human organism in a manner appearing to be beyond the merely mechanical. AI is largely a matter of computer programming, in which stored records of past experience are made to modify future responses, but it also encompasses research into humanoid methods of data acquisition, the use of fuzzy logic and of artificial neural networks.
Collins Dictionary of Medicine © Robert M. Youngson 2004, 2005
References in periodicals archive ?
This report provides an in-depth analysis of the market structure along with detailed segmentation of the Machine Intelligence market.
With its Machine Intelligence strategy, Ericsson intends to move away from stand-alone on-premise analytics applications, which are typically slow and costly, in favor of adopting MI-based aaS offerings and implementations.
His goal: supply assured PNT, processed with machine intelligence and supported with new location technologies, without service members ever knowing machine intelligence had intervened to keep them oriented and operational.
According to Franchise Times, it is likely that machine intelligence will soon connect consumers' assistant services such as Apple's Siri to retail POS systems.
In general, conventional machine intelligence includes three phases, such as signal sensing, signal processing, and signal recognition, which are also termed as low-level acquisition, middle-level representation, and high-level analysis.
Nutonian's machine intelligence application, Eureqa, empowers business intelligence professionals to do the work of data scientists.
Machine intelligence is helping to solve problems in business and society by interpreting large amounts of data quickly, for instance: detecting diseases, biodiversity conservation and smart virtual assistants to help with organisation.
He showed how these methods can enable people and machines to work closely together as coordinated teams to solve problems, taking advantage of the complementarities of human and machine intelligence. He has also played a leadership role in the development and fielding of practical applications.
A new report by the Leading Edge Forum (LEF), announced at their US Executive Forum in Washington DC, explains why Machine Intelligence (MI) is taking off today.
It balances out the risk elements with the positive elements and both systems work hand in hand using machine intelligence, algorithms to compile this data providing context in real-time, happening all in a matter of milliseconds.
In the meanwhile machine intelligence has progressed phenomenally.
Machine- to-machine intelligence is becoming more important because we need to do all of these things at scale as we need to scan a lot of data in a matter of milliseconds, so we will see a lot more for machine intelligence and machine learning in the future.