Study Design and Population: This retrospective study assessed the effectiveness of a commercial AI tool in correctly identifying unremarkable chest radiographs, thus potentially reducing the workload in radiology departments. The study analyzed 1,961 chest radiographs from adult patients (median age: 72 years) across four Danish hospitals. The radiographs were labeled as remarkable or unremarkable by […]

The post Retrospective Study: AI Tool Accurately Excludes Pathology in Up to 52.7% of Unremarkable Chest Radiographs with Low Critical Misses – Radiology appeared first on Links Medicus.