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Abstract Objective To solve the problems of insufficient model generalization ability and unclear influence of anatomical regional differences in the intelligent diagnosis of spinal tuberculosis, and to construct a multi-center CT deep learning model. Method This study adopted a retrospective multi-center design and collected CT images of 1025 patients with spinal tuberculosis from 4 hospitals in the southwest region from 2012 to 2024.
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