Multi-Site Assessment of Pediatric Bone Age Using Deep Learning-Reference-Cited by-同舟云学术

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Multi-Site Assessment of Pediatric Bone Age Using Deep Learning

Published:2020-09-21 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 11th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics
language:
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Author:

Valliani Aly A.¹,Schwartz John T.¹,Arvind Varun¹,Taree Amir¹,Kim Jun S.¹,Cho Samuel K.¹

Affiliation:

1. Department of Orthopedic Surgery, Icahn School of Medicine at Mount Sinai, New York, New York

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3388440.3412429

Reference30 articles.

1. Bone age assessment: a large scale comparison of the Greulich and Pyle, and Tanner and Whitehouse (TW2) methods

2. Ethnic and sex differences in skeletal maturation among the Birth to Twenty cohort in South Africa

3. Bone Age;Creo Ana L;A Handy Tool for Pediatric Providers. Pediatrics,2017

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

5. Progression or not progression? How to deal with adolescent idiopathic scoliosis during puberty

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