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Tytuł:
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Basic Artificial Intelligence Techniques: Machine Learning and Deep Learning.
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Autorzy:
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Erickson BJ; Department of Radiology, Mayo Clinic, Mayo Building East 2, 200 First Street Southwest, Rochester, MN 55905, USA. Electronic address: .
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Źródło:
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Radiologic clinics of North America [Radiol Clin North Am] 2021 Nov; Vol. 59 (6), pp. 933-940.
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Typ publikacji:
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Journal Article; Review
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Język:
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English
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Imprint Name(s):
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Original Publication: Philadelphia, London, Saunders.
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MeSH Terms:
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Machine Learning*
Diagnostic Imaging/*methods
Image Interpretation, Computer-Assisted/*methods
Artificial Intelligence ; Deep Learning ; Humans
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Contributed Indexing:
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Keywords: Convolutional neural network; Deep learning; Feature engineering; U-net
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Entry Date(s):
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Date Created: 20211025 Date Completed: 20211028 Latest Revision: 20211028
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Update Code:
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20240105
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DOI:
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10.1016/j.rcl.2021.06.004
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PMID:
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34689878
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Machine learning is an important tool for extracting information from medical images. Deep learning has made this more efficient by not requiring an explicit feature extraction step and in some cases detecting features that humans had not identified. The rapid advance of deep learning technologies continues to result in valuable tools. The most effective use of these tools will occur when developers also understand the properties of medical images and the clinical questions at hand. The performance metrics also are critical for guiding the training of an artificial intelligence and for assessing and comparing its tools.
Competing Interests: Disclosure B.J. Erickson is a founder and stockholder in FLowSIGMA, Inc.
(Copyright © 2021 Elsevier Inc. All rights reserved.)