Artificial Intelligence-Enabled Point-of-Care Echocardiography: Bringing Precision Imaging to the Bedside

被引:0
作者
East, Sasha-ann [1 ]
Wang, Yanting [1 ]
Yanamala, Naveena [1 ]
Maganti, Kameswari [1 ]
Sengupta, Partho P. [1 ]
机构
[1] Rutgers Robert Wood Johnson Med Sch, Dept Med, Div Cardiovasc Dis & Hypertens, 125 Paterson St, New Brunswick, NJ 08901 USA
基金
美国国家科学基金会; 美国安德鲁·梅隆基金会;
关键词
Artificial intelligence; Point-of-care ultrasound; Deep learning; Generative AI; ULTRASOUND; STANDARD;
D O I
10.1007/s11883-025-01316-9
中图分类号
R6 [外科学];
学科分类号
1002 ; 100210 ;
摘要
Purpose of ReviewThe integration of artificial intelligence (AI) with point-of-care ultrasound (POCUS) is transforming cardiovascular diagnostics by enhancing image acquisition, interpretation, and workflow efficiency. These advancements hold promise in expanding access to cardiovascular imaging in resource-limited settings and enabling early disease detection through screening applications. This review explores the opportunities and challenges of AI-enabled POCUS as it reshapes the landscape of cardiovascular imaging.Recent FindingsAI-enabled systems can reduce operator dependency, improve image quality, and support clinicians-both novice and experienced-in capturing diagnostically valuable images, ultimately promoting consistency across diverse clinical environments. However, widespread adoption faces significant challenges, including concerns around algorithm generalizability, bias, explainability, clinician trust, and data privacy. Addressing these issues through standardized development, ethical oversight, and clinician-AI collaboration will be critical to safe and effective implementation.SummaryLooking ahead, emerging innovations-such as autonomous scanning, real-time predictive analytics, tele-ultrasound, and patient-performed imaging-underscore the transformative potential of AI-enabled POCUS in reshaping cardiovascular care and advancing equitable healthcare delivery worldwide.
引用
收藏
页数:10
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