Bone Age Estimation and Prediction of Final Adult Height Using Deep Learning.

ABSTRACT:

Purpose

The appropriate evaluation of height and accurate estimation of bone age are crucial for proper assessment of the growth status of a child. We developed a bone age estimation program using a deep learning algorithm and established a model to predict the final adult height of Korean children.

Materials and methods

A total of 1678 radiographs from 866 children, for which the interpretation results were consistent between two pediatric endocrinologists, were used to train and validate the deep learning model. The bone age estimation algorithm was based on the convolutional neural network of the deep learning system. The test set simulation was performed by a deep learning program and two raters using 150 radiographs and final height data for 100 adults.

Results

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SUBMITTER: Suh J 

PROVIDER: S-EPMC10613764 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature