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Radiología (English Edition)
Article . 2022 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
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Artificial Intelligence in Radiology: an introduction to the most important concepts

Authors: Pérez del Barrio, A.; Menéndez Fernández-Miranda, Pablo; Sanz Bellón, Pablo; Lloret Iglesias, Lara; Rodriguez Rodriguez, D.;

Artificial Intelligence in Radiology: an introduction to the most important concepts

Abstract

The interpretation of medical imaging tests is one of the main tasks that radiologists do. For years, it has been a challenge to teach computers to do this kind of cognitive task; the main objective of the field of computer vision is to overcome this challenge. Thanks to technological advances, we are now closer than ever to achieving this goal, and radiologists need to become involved in this effort to guarantee that the patient remains at the center of medical practice. This article clearly explains the most important theoretical concepts in this area and the main problems or challenges at the present time; moreover, it provides practical information about the development of an artificial intelligence project in a radiology department.

Keywords

Radiography, Artificial Intelligence, Radiologists, Humans, Radiology

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
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3
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