The Use of Artificial Intelligence in the Evaluation of Knee Pathology.

Autor:	Garwood ER; Division of Musculoskeletal Imaging and Intervention, Department of Radiology, University of Massachusetts Memorial Medical Center and University of Massachusetts Medical School, Worcester, Massachusetts., Tai R; Division of Musculoskeletal Imaging and Intervention, Department of Radiology, University of Massachusetts Memorial Medical Center and University of Massachusetts Medical School, Worcester, Massachusetts., Joshi G; Division of Musculoskeletal Imaging and Intervention, Department of Radiology, University of Massachusetts Memorial Medical Center and University of Massachusetts Medical School, Worcester, Massachusetts., Watts V GJ; Division of Musculoskeletal Imaging and Intervention, Department of Radiology, University of Massachusetts Memorial Medical Center and University of Massachusetts Medical School, Worcester, Massachusetts.
Jazyk:	angličtina
Zdroj:	Seminars in musculoskeletal radiology [Semin Musculoskelet Radiol] 2020 Feb; Vol. 24 (1), pp. 21-29. Date of Electronic Publication: 2020 Jan 28.
DOI:	10.1055/s-0039-3400264
Abstrakt:	Artificial intelligence (AI) holds the potential to revolutionize the field of radiology by increasing the efficiency and accuracy of both interpretive and noninterpretive tasks. We have only just begun to explore AI applications in the diagnostic evaluation of knee pathology. Experimental algorithms have already been developed that can assess the severity of knee osteoarthritis from radiographs, detect and classify cartilage lesions, meniscal tears, and ligament tears on magnetic resonance imaging, provide automatic quantitative assessment of tendon healing, detect fractures on radiographs, and predict those at highest risk for recurrent bone tumors. This article reviews and summarizes the most current literature. Competing Interests: None declared. (Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.)
Databáze:	MEDLINE
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