Artificial Intelligence in Point-of-Care Ultrasound.
Authors
Affiliations (3)
Affiliations (3)
- Division of Pulmonary, Allergy & Critical Care Medicine, Stanford Health Care, Palo Alto, CA, USA.
- Division of Critical Care Medicine, London Health Sciences Centre, London, ON, Canada.
- Division of Critical Care Medicine, University of Ottawa / The Ottawa Hospital, Ottawa, ON, Canada.
Abstract
Artificial intelligence (AI) is increasingly integrated into point-of-care ultrasound (POCUS) to enhance its utility in critical care settings. This manuscript explores the current state of AI applications in POCUS, focusing on key domains such as image acquisition, image interpretation, education, task automation, procedural guidance, program development, and quality assurance. AI-driven tools can potentially improve image quality, provide real-time feedback, and assist in the interpretation of ultrasound images, thereby democratizing the use of POCUS across varying levels of operator expertise. This narrative review highlights relevant studies demonstrating the clinical utility of AI in POCUS, discusses the challenges that remain, and provides insights into future developments. The goal is to equip intensivists with a comprehensive understanding of how AI can support POCUS practice today and what advancements are on the horizon.