Artificial Intelligence in Medicine: Beginner’s Guide
Artificial intelligence is expected to influence clinical practice substantially in the foreseeable future. Despite all the excitement around the technology, it cannot be denied that the application of artificial intelligence in medicine is overhyped. In fact, artificial intelligence for medicine...
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The Korean Society of Radiology
2018-05-01
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Online Access: | https://doi.org/10.3348/jksr.2018.78.5.301 |
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doaj-a458a5f9cca74cbe9834e8b843e21d392020-11-25T01:34:39ZengThe Korean Society of Radiology대한영상의학회지1738-26372288-29282018-05-01785301308https://doi.org/10.3348/jksr.2018.78.5.301Artificial Intelligence in Medicine: Beginner’s GuideSeong Ho Park0Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, KoreaArtificial intelligence is expected to influence clinical practice substantially in the foreseeable future. Despite all the excitement around the technology, it cannot be denied that the application of artificial intelligence in medicine is overhyped. In fact, artificial intelligence for medicine is presently in its infancy, and very few are currently in clinical use. To best leverage the potential of this technology to improve patient care, clinicians need to see beyond the hype, as the guidance and leadership of medical professionals are critical in this matter. To this end, medical professionals must understand the underlying technological basics of artificial intelligence, as well as the methodologies of its proper clinical validation. They should also have an impartial, complete view of the capabilities, pitfalls, and limitations of the technology and its use in healthcare. The present article provides succinct explanations of these matters and suggests further reading materials (peer-reviewed articles and web pages) for medical professionals who are unfamiliar with artificial intelligence.https://doi.org/10.3348/jksr.2018.78.5.301artificial intelligencemachine learningmedicinemedical imagingdiagnoses |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Seong Ho Park |
spellingShingle |
Seong Ho Park Artificial Intelligence in Medicine: Beginner’s Guide 대한영상의학회지 artificial intelligence machine learning medicine medical imaging diagnoses |
author_facet |
Seong Ho Park |
author_sort |
Seong Ho Park |
title |
Artificial Intelligence in Medicine: Beginner’s Guide |
title_short |
Artificial Intelligence in Medicine: Beginner’s Guide |
title_full |
Artificial Intelligence in Medicine: Beginner’s Guide |
title_fullStr |
Artificial Intelligence in Medicine: Beginner’s Guide |
title_full_unstemmed |
Artificial Intelligence in Medicine: Beginner’s Guide |
title_sort |
artificial intelligence in medicine: beginner’s guide |
publisher |
The Korean Society of Radiology |
series |
대한영상의학회지 |
issn |
1738-2637 2288-2928 |
publishDate |
2018-05-01 |
description |
Artificial intelligence is expected to influence clinical practice substantially in the
foreseeable future. Despite all the excitement around the technology, it cannot be
denied that the application of artificial intelligence in medicine is overhyped. In fact,
artificial intelligence for medicine is presently in its infancy, and very few are currently in clinical use. To best leverage the potential of this technology to improve
patient care, clinicians need to see beyond the hype, as the guidance and leadership
of medical professionals are critical in this matter. To this end, medical professionals
must understand the underlying technological basics of artificial intelligence, as
well as the methodologies of its proper clinical validation. They should also have an
impartial, complete view of the capabilities, pitfalls, and limitations of the technology and its use in healthcare. The present article provides succinct explanations of
these matters and suggests further reading materials (peer-reviewed articles and
web pages) for medical professionals who are unfamiliar with artificial intelligence. |
topic |
artificial intelligence machine learning medicine medical imaging diagnoses |
url |
https://doi.org/10.3348/jksr.2018.78.5.301 |
work_keys_str_mv |
AT seonghopark artificialintelligenceinmedicinebeginnersguide |
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