Expanding the applications of artificial intelligence in emergency radiology: Advancing precision medicine and resource efficiency

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Authors: Zhenxing He, Jie Wang, Jian-She Yang
Cited by: 1
References: 19

Abstract

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.

Fields of Study & Subjects

Artificial Intelligence in Healthcare and Education COVID-19 diagnosis using AI Radiology practices and education

Publication details

Journal / source
World Journal of Radiology
Publisher
Baishideng Publishing Group Inc.
Volume
18
Issue
1
Pages
117814–117814
Publication date
24 January 2026
Language
EN