Artificial Intelligence in Emergency Radiology: Current Applications, Challenges, and Future Directions
Abstract This is a narrative review of recent peer-reviewed literature on artificial intelligence (AI) in emergency imaging spanning patient scheduling, image optimization, detection of critical findings, communication, and regulatory oversight. We review the current AI applications in emergency radiology and summarize clinically meaningful performance metrics. There are multiple instances of high performance in identifying imaging findings and prioritizing worklists, but limited prospective data demonstrating patient outcome improvements. We discuss the challenges in going from AI model performance to better outcomes, including the impact of false positives on workflow, ethical and regulatory issues, and implementation challenges. Practical tips for the evaluation, adoption, and monitoring of AI tools are outlined. Regulatory frameworks are in evolution and lag this rapidly changing landscape. Radiologist oversight remains critical at all steps to ensure safe and effective use of AI tools.