Applications of Artificial Intelligence in Acute Abdominal Imaging

Author:

Yao Jason1,Chu Linda C.2,Patlas Michael3ORCID

Affiliation:

1. Department of Radiology, McMaster University, Hamilton, ON, Canada

2. Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA

3. Department of Medical Imaging, University of Toronto, Toronto, ON, Canada

Abstract

Artificial intelligence (AI) is a rapidly growing field with significant implications for radiology. Acute abdominal pain is a common clinical presentation that can range from benign conditions to life-threatening emergencies. The critical nature of these situations renders emergent abdominal imaging an ideal candidate for AI applications. CT, radiographs, and ultrasound are the most common modalities for imaging evaluation of these patients. For each modality, numerous studies have assessed the performance of AI models for detecting common pathologies, such as appendicitis, bowel obstruction, and cholecystitis. The capabilities of these models range from simple classification to detailed severity assessment. This narrative review explores the evolution, trends, and challenges in AI applications for evaluating acute abdominal pathologies. We review implementations of AI for non-traumatic and traumatic abdominal pathologies, with discussion of potential clinical impact, challenges, and future directions for the technology.

Publisher

SAGE Publications

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Artificial Intelligence in Acute Abdominal Imaging: Are We Reaching the Grail?;Canadian Association of Radiologists Journal;2024-06-10

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