Briody Hayley, Hanneman Kate, Patlas Michael N
Department of Radiology, Beaumont Hospital, Dublin, Ireland.
Department of Medical Imaging, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada.
Can Assoc Radiol J. 2025 Aug;76(3):454-465. doi: 10.1177/08465371251322705. Epub 2025 Feb 19.
The applications of artificial intelligence (AI) in radiology are rapidly advancing with AI algorithms being used in a wide range of disease pathologies and clinical settings. Acute thoracic pathologies including rib fractures, pneumothoraces, and acute PE are associated with significant morbidity and mortality and their identification is crucial for prompt treatment. AI models which increase diagnostic accuracy, improve radiologist efficiency and reduce time to diagnosis of acute abnormalities in the thorax have the potential to significantly improve patient outcomes. The purpose of this review is to summarize the current applications of AI in acute thoracic imaging, highlighting their strengths, limitations, and future research opportunities.
人工智能（AI）在放射学中的应用正在迅速发展，AI算法被广泛应用于各种疾病病理和临床场景。包括肋骨骨折、气胸和急性肺栓塞在内的急性胸部疾病具有较高的发病率和死亡率，对其进行识别对于及时治疗至关重要。提高诊断准确性、提高放射科医生效率并缩短胸部急性异常诊断时间的AI模型有可能显著改善患者预后。本综述的目的是总结AI在急性胸部成像中的当前应用，突出其优势、局限性和未来的研究机会。
