AIMC Topic: Artificial Intelligence

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Artificial intelligence and augmented reality in gynecology.

Current opinion in obstetrics & gynecology
PURPOSE OF REVIEW: Artificial intelligence and augmented reality have been progressively incorporated into our daily life. Technological advancements have resulted in the permeation of similar systems into medical practice.

Designing and executing a functional exercise to test a novel informatics tool for mass casualty triage.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: The testing of informatics tools designed for use during mass casualty incidents presents a unique problem as there is no readily available population of victims or identical exposure setting. The purpose of this article is to describe the...

Artificial Intelligent Model With Neural Network Machine Learning for the Diagnosis of Orthognathic Surgery.

The Journal of craniofacial surgery
Diagnosis and treatment planning are the most important steps in the orthognathic surgery for the successful treatment. The purpose of this study was to develop a new artificial intelligent model for surgery/non-surgery decision and extraction determ...

Artificial intelligence in reproductive medicine.

Reproduction (Cambridge, England)
Artificial intelligence (AI) has experienced rapid growth over the past few years, moving from the experimental to the implementation phase in various fields, including medicine. Advances in learning algorithms and theories, the availability of large...

[Study on the Clinical Evaluation of Image-based Artificial Intelligence Aided Diagnosis Software Approved in the United States].

Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation
Artificial intelligence, as the breakthrough of current information technology, is gaining importance and being applied in more and more industries. Research on the application of artificial intelligence to the medical field has gradually matured and...

Engineering a Less Artificial Intelligence.

Neuron
Despite enormous progress in machine learning, artificial neural networks still lag behind brains in their ability to generalize to new situations. Given identical training data, differences in generalization are caused by many defining features of a...

[Chapter 6. Hybridisation of networks.].

Journal international de bioethique et d'ethique des sciences
Prompted by the digital revolution, the hybridisation of networks, terrestrial and on satellites, opens the door to a world of convergences, dominated by the Internet of Objects and the development of artificial intelligence.