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JointNET: A Deep Model for Predicting Active Sacroiliitis from Sacroiliac Joint Radiography

By Sevcan Turk and others
Purpose: To develop a deep learning model that predicts active inflammation from sacroiliac joint radiographs and to compare the success with radiologists. Materials and Methods: A total of 1,537 (augmented 1752) grade 0 SIJs of 768 patients were retrospectively analyzed. Gold-standard MRI exams showed active inflammation in 330 joints according... Show more
January 27, 2023
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JointNET: A Deep Model for Predicting Active Sacroiliitis from Sacroiliac Joint Radiography
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