Artificial intelligence improves resident detection of pediatric and young adult upper extremity fractures-Reference-Cited by-同舟云学术

Artificial intelligence improves resident detection of pediatric and young adult upper extremity fractures

Published:2024-05-02 Issue: Volume: Page:
ISSN:0364-2348
Container-title:Skeletal Radiology
language:en
Short-container-title:Skeletal Radiol

Author:

Zech John R.,Ezuma Chimere O.,Patel Shreya,Edwards Collin R.,Posner Russell,Hannon Erin,Williams Faith,Lala Sonali V.,Ahmad Zohaib Y.,Moy Matthew P.,Wong Tony T.

Funder

RSNA Research and Education Foundation

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s00256-024-04698-0.pdf

Reference27 articles.

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3. George MP, Bixby S. Frequently missed fractures in pediatric trauma: a pictorial review of plain film radiography. Radiol Clin North Am. 2019;57:843–55.

4. Baig MN. A review of epidemiological distribution of different types of fractures in paediatric age. Cureus. 2017;9:e1624.

5. Kitamura G, Chung CY, Moore BE 2nd. Ankle fracture detection utilizing a convolutional neural network ensemble implemented with a small sample, de novo training, and multiview incorporation. J Digit Imaging. 2019;32:672–7.

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