Rouzrokh P, Wyles CC, Philbrick KA, et al. - This study was sought to create a deep learning tool to automate the measurement of acetabular component angles on postoperative radiographs. Researchers used two cohorts of 600 anteroposterior (AP) pelvis and 600 cross-table lateral hip postoperative radiographs to establish deep learning models to segment the acetabular component and the ischial tuberosities. They investigated the performance of the tool on 80 AP and 80 cross-table lateral radiographs. A highly accurate deep learning tool was established to automate the measurement of the angular position of acetabular components for use in both clinical and research settings.