Doctor Bone: training neural networks to assist in determining bone age
DOI:
https://doi.org/10.59681/2175-4411.v16.iEspecial.2024.1382Keywords:
Bone Age, Diagnostic Aid, Artificial intelligenceAbstract
Objective: To explore the application of artificial intelligence (AI) in predicting bone age from X-ray images. Method: The Interdisciplinary Methodology for the Development of Health Technologies (MIDTS) was used to develop a prediction tool. Training was conducted with convolutional neural networks (CNNs) using a dataset of 14,036 X-ray images. Results: The tool achieved a coefficient of determination (R²) of 0.94807 and a Mean Absolute Error (MAE) of 6.97, highlighting its accuracy and clinical potential. Conclusion: The project demonstrated great potential to enhance bone age prediction, with possibilities for evolution as the database grows and AI becomes more sophisticated.
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