The Promise of Artificial Intelligence-Assisted Point-of-Care Ultrasonography in Perioperative Care

被引：6

作者：

Serrano, Ricardo A. ^{[1
,2
]}

Smeltz, Alan M. ^{[1
]}

机构：

[1] Univ N Carolina, Sch Med, Chapel Hill, NC USA

[2] N2198 Univ North Carolina Hosp, CB 7010, Chapel Hill, NC 27599 USA

来源：

JOURNAL OF CARDIOTHORACIC AND VASCULAR ANESTHESIA | 2024年 / 38卷 / 05期

关键词：

point of care ultrasound; artificial intelligence; machine learning; medical imaging; LUNG ULTRASOUND; ANESTHESIA; GUIDE; STATE; AI;

D O I：

10.1053/j.jvca.2024.01.034

中图分类号：

R614 [麻醉学];

学科分类号：

100217 ;

摘要：

The role of point-of-care ultrasonography in the perioperative setting has expanded rapidly over recent years. Revolutionizing this technology further is integrating artificial intelligence to assist clinicians in optimizing images, identifying anomalies, performing automated measurements and calculations, and facilitating diagnoses. Artificial intelligence can increase point-of-care ultrasonography efficiency and accuracy, making it an even more valuable point-of-care tool. Given this topic's importance and ever-changing landscape, this review discusses the latest trends to serve as an introduction and update in this area. (c) 2024 Elsevier Inc. All rights reserved.

引用

页码：1244 / 1250

页数：7

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