Published online Jan 28, 2026. doi: 10.4329/wjr.v18.i1.117814
Revised: January 12, 2026
Accepted: January 15, 2026
Published online: January 28, 2026
Processing time: 40 Days and 22.2 Hours
Owing to their swift, precise, and tireless capabilities, artificial intelligence (AI) applications in emergency radiology are becoming powerful tools for radiologists. These applications, which are useful for improving diagnostic efficiency, are also a core engine driving the entire field of emergency medicine toward higher levels of precision, personalization, and efficiency. The integration of AI into emergency radiology thus represents a transformative advancement in precision medicine. We explore herein the expanding applications of AI in emergency radiology, focusing on their potential to enhance diagnostic accuracy, streamline workflows, and improve patient outcomes. By analyzing its current utilization and future directions, we demonstrate how AI is revolutionizing emergency care through intelligent image analysis and decision support systems. Although certain challenges remain, including data security, model interpretability, and clinical implementation standards, the immense potential of AI to reshape emergency workflows, promote precision medicine, and improve patient outcomes is unmistakable.
Core Tip: With emerging technologies such as quantum computing and federated learning poised to revolutionize diagnostic capabilities, the future of artificial intelligence in emergency radiology is promising. These innovations will enable the rapid processing of complex imaging data and support precision medicine tailored to individual patient needs. By overcoming current challenges and leveraging current and future advancements in artificial intelligence, emergency radiology will achieve new heights in precision medicine, ultimately enhancing patient care and operational efficiency.