谷歌浏览器插件
订阅小程序
在清言上使用

Ten conditions where lung ultrasonography may fail: limits, pitfalls and lessons learned from a computer-aided algorithmic approach

MINERVA ANESTESIOLOGICA(2022)

引用 3|浏览14
暂无评分
摘要
Lung ultrasonography provides relevant information on morphological and functional changes occurring in the lungs. However, it correlates weakly with pulmonary congestion and extra vascular lung water. Moreover, there is lack of consensus on scoring systems and acquisition protocols. The automation of this technique may provide promising easy-to use clinical tools to reduce inter-and intra-observer variability and to standardize scores, allowing faster data collection without increased costs and patients risks. (Cite this article as: Corradi F, Vetrugno L, Isirdi A, Bignami E, Boccacci P, Forfori F. Ten conditions where lung ultrasonography may fail: limits, pitfalls and lessons learned from a computer-aided algorithmic approach. Minerva Anestesiol 2022;88:308-13. DOI: 10.23736/S0375-9393.22.16195-X)
更多
查看译文
关键词
Computer-assisted diagnosis, Artificial intelligence, Respiratory insufficiency, Differential diagnosis, COVID-19, Extravascular lung water
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要