The uncovered biases and errors in clinical determination of bone age by using deep learning models-Reference-Cited by-同舟云学术

The uncovered biases and errors in clinical determination of bone age by using deep learning models

Published:2022-12-20 Issue:5 Volume:33 Page:3544-3556
ISSN:1432-1084
Container-title:European Radiology
language:en
Short-container-title:Eur Radiol

Author:

Bai Mei,Gao Liangxin,Ji Min,Ge Jianbang,Huang Lingyun,Qiao HaoChen,Xiao Jing,Chen Xiaotian,Yang Bin,Sun Yingqi,Zhang Minjie,Zhang Wenjie,Luo Feihong,Yang Haowei,Mei Haibing,Qiao Zhongwei^ORCID

Publisher

Springer Science and Business Media LLC

Subject

Radiology, Nuclear Medicine and imaging,General Medicine

Link

https://link.springer.com/content/pdf/10.1007/s00330-022-09330-0.pdf

Reference31 articles.

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2. Greulich WW, Pyle SI (1959) Radiographic atlas of skeletal development of the hand and wrist, 2nd edn. Stanford University Press, Stanford, California

3. Van Rijn RR, Thodberg HH (2013) Bone age assessment: automated techniques coming of age? Acta Radiol 54:1024–1029

4. Lee H, Tajmir S, Lee J et al (2017) Fully automated deep learning system for bone age assessment. J Digit Imaging 30:427–441

5. Summers RM (2018) Deep learning lends a hand to pediatric radiology. Radiology 287:323–325

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