Assessing Bone Age: A Paradigm for the Next Generation of Artificial Intelligence in Radiology-Reference-Cited by-同舟云学术

Assessing Bone Age: A Paradigm for the Next Generation of Artificial Intelligence in Radiology

Published:2021-12 Issue:3 Volume:301 Page:700-701
ISSN:0033-8419
Container-title:Radiology
language:en
Short-container-title:Radiology

Author:

Rubin David A.¹^ORCID

Affiliation:

1. From the Department of Radiology, NYU Grossman School of Medicine, 160 E 34th St, New York, NY 10016; All Pro Orthopedic Imaging Consultants, St Louis, Mo; and Radsource, Brentwood, Tenn.

Publisher

Radiological Society of North America (RSNA)

Subject

Radiology, Nuclear Medicine and imaging

Link

http://pubs.rsna.org/doi/pdf/10.1148/radiol.2021211339

Reference9 articles.

1. RADIOGRAPHIC ATLAS OF SKELETAL DEVELOPMENT OF THE HAND AND WRIST

2. Bone age assessment with various machine learning techniques: A systematic literature review and meta-analysis

3. The RSNA Pediatric Bone Age Machine Learning Challenge

4. Artificial Intelligence Algorithm Improves Radiologist Performance in Skeletal Age Assessment: A Prospective Multicenter Randomized Controlled Trial

5. Effect of Knowledge of Chronologic Age on the Variability of Pediatric Bone Age Determined Using the Greulich and Pyle Standards

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