Automated detection and classification of the proximal humerus fracture by using deep learning algorithm

Background and purpose - We aimed to evaluate the ability of artificial intelligence (a deep learning algorithm) to detect and classify proximal humerus fractures using plain anteroposterior shoulder radiographs. Patients and methods - 1,891 images (1 image per person) of normal shoulders (n = 515)...

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Vydané v:	Acta orthopaedica Ročník 89; číslo 4; s. 468 - 473
Hlavní autori:	Chung, Seok Won, Han, Seung Seog, Lee, Ji Whan, Oh, Kyung-Soo, Kim, Na Ra, Yoon, Jong Pil, Kim, Joon Yub, Moon, Sung Hoon, Kwon, Jieun, Lee, Hyo-Jin, Noh, Young-Min, Kim, Youngjun
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	England Taylor & Francis 04.07.2018 Medical Journals Sweden
Predmet:	Adult Aged Aged, 80 and over Algorithms Area Under Curve Arthrography Deep Learning Female Humans Male Middle Aged Shoulder Fractures - classification Shoulder Fractures - diagnostic imaging Young Adult
ISSN:	1745-3674, 1745-3682, 1745-3682
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