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Deep learning (DL) happens to be recommended for the automatic dimension of leg size discrepancy (LLD) on radiographs, which may free up time for pediatric radiologists to focus on value-adding tasks. The goal of our research would be to develop a unified answer using DL both for automatic LLD dimensions and extensive tests in a large and extensive radiographic dataset addressing young ones at all stages, from infancy to adolescence, and with ma
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