AI Reduces Missed Findings: Results from MGH Study

Chest radiography, also known as a chest X-ray (CXR), is a widely used imaging test for the screening, diagnosis, and monitoring of various cardiothoracic disorders. According to estimates, CXRs make up around 20% of all imaging exams, with millions of CXRs performed in the United States alone each year. Despite its widespread use, CXR interpretation is subjective and prone to wide interobserver inconsistencies. This can lead to missed findings, which can have serious implications, as 19% of early lung cancers that present as nodules on CXRs are missed. To address this issue, researchers from Massachusetts General Hospital and Harvard Medical School, Qure.ai, and CARPL conducted a study to evaluate the frequency of missed findings in CXRs and the potential of artificial intelligence (AI) to reduce missed findings.