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Background:Trauma patients present with heterogeneous injury patterns that are challenging to represent in statistical models. Traditional approaches either use high-dimensional one-hot encoding, resulting in sparse features, or aggregate injuries into summary scores that lose patient-specific detail.Objective:This study developed data-driven ICD-10 embeddings for trauma injuries and evaluated the
