Researchers have developed a multi-agent AI system that can structure and quality-assure radiology reports. The system uses natural language processing to identify and correct errors in the report's format and content. In a retrospective study of 638 reports, the system correctly structured all reports into standardized sections and detected mismatches between different parts of the report. Two board-certified radiologists evaluated a subset of 45 reports and found that the system performed well, with only 4% incorrectly restructured. The researchers conclude that such systems could support standardization of reporting and quality assurance in radiology practice. --- Why it matters: This matters to AI engineers because it demonstrates the potential for multi-agent systems to improve the accuracy and consistency of medical reports, which can have significant implications for patient care. It also highlights the importance of developing AI systems that can work together to perform complex tasks. Source: https://arxiv.org/abs/2608.18072