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Generalizability and Bias in a Deep Learning Pediatric Bone Age Prediction Model Using Hand Radiographs

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References

2017Performance of a Deep-Learning Neural Network Model in Assessing Skeletal Maturity on Pediatric Hand Radiographs456 cited
1996Bone age in children of diverse ethnicity.238 cited
2007Bone age assessment of children using a digital hand atlas214 cited
2008Racial Differences in Growth Patterns of Children Assessed on the Basis of Bone Age190 cited
2018MABAL: a Novel Deep-Learning Architecture for Machine-Assisted Bone Age Labeling90 cited
2001Effect of Knowledge of Chronologic Age on the Variability of Pediatric Bone Age Determined Using the Greulich and Pyle Standards86 cited
2013The applicability of Greulich and Pyle atlas to assess skeletal age for four ethnic groups77 cited

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2025Bone Age Assessment Using Various Medical Imaging Techniques Enhanced by Artificial Intelligence20 cited
2023Artificial Intelligence (AI)-Based Systems for Automatic Skeletal Maturity Assessment through Bone and Teeth Analysis: A Revolution in the Radiological Workflow?15 cited
2025Artificial Intelligence-Based Models for Automated Bone Age Assessment from Posteroanterior Wrist X-Rays: A Systematic Review12 cited
2025Determination of Skeletal Age From Hand Radiographs Using Deep Learning9 cited

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