护理点超声中的人工智能概述。呼吸系统诊断的新视野。

IF 1.6 Q2 ANESTHESIOLOGY
Sławomir Mika, Wojciech Gola, Monika Gil-Mika, Mateusz Wilk, Hanna Misiołek
{"title":"护理点超声中的人工智能概述。呼吸系统诊断的新视野。","authors":"Sławomir Mika, Wojciech Gola, Monika Gil-Mika, Mateusz Wilk, Hanna Misiołek","doi":"10.5114/ait.2024.136784","DOIUrl":null,"url":null,"abstract":"<p><p>Throughout the past decades ultrasonography did not prove to be a procedure of choice if regarded as part of the routine bedside examination. The reason was the assumption defining the lungs and the bone structures as impenetrable by ultrasound. Only during the recent several years has the approach to the use of such tool in clinical daily routines changed dramatically to offer so-called point-of-care ultrasonography (POCUS). Both vertical and horizontal artefacts became valuable sources of information about the patient's clinical condition, assisting therefore the medical practitioner in differential diagnosis and monitoring of the patient. What is important is that the information is delivered in real time, and the procedure itself is non-invasive. The next stage marking the progress made in this area of diagnostic imaging is the development of arti-ficial intelligence (AI) based on machine learning algorithms. This article is intended to present the available, innovative solutions of the ultrasound systems, including Smart B-line technology, to ensure automatic identification process, as well as interpretation of B-lines in the given lung area of the examined patient. The article sums up the state of the art in ultrasound artefacts and AI applied in POCUS.</p>","PeriodicalId":7750,"journal":{"name":"Anaesthesiology intensive therapy","volume":"56 1","pages":"1-8"},"PeriodicalIF":1.6000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11022635/pdf/","citationCount":"0","resultStr":"{\"title\":\"Overview of artificial intelligence in point-of-care ultrasound. New horizons for respiratory system diagnoses.\",\"authors\":\"Sławomir Mika, Wojciech Gola, Monika Gil-Mika, Mateusz Wilk, Hanna Misiołek\",\"doi\":\"10.5114/ait.2024.136784\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Throughout the past decades ultrasonography did not prove to be a procedure of choice if regarded as part of the routine bedside examination. The reason was the assumption defining the lungs and the bone structures as impenetrable by ultrasound. Only during the recent several years has the approach to the use of such tool in clinical daily routines changed dramatically to offer so-called point-of-care ultrasonography (POCUS). Both vertical and horizontal artefacts became valuable sources of information about the patient's clinical condition, assisting therefore the medical practitioner in differential diagnosis and monitoring of the patient. What is important is that the information is delivered in real time, and the procedure itself is non-invasive. The next stage marking the progress made in this area of diagnostic imaging is the development of arti-ficial intelligence (AI) based on machine learning algorithms. This article is intended to present the available, innovative solutions of the ultrasound systems, including Smart B-line technology, to ensure automatic identification process, as well as interpretation of B-lines in the given lung area of the examined patient. The article sums up the state of the art in ultrasound artefacts and AI applied in POCUS.</p>\",\"PeriodicalId\":7750,\"journal\":{\"name\":\"Anaesthesiology intensive therapy\",\"volume\":\"56 1\",\"pages\":\"1-8\"},\"PeriodicalIF\":1.6000,\"publicationDate\":\"2024-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11022635/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Anaesthesiology intensive therapy\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5114/ait.2024.136784\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ANESTHESIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Anaesthesiology intensive therapy","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5114/ait.2024.136784","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ANESTHESIOLOGY","Score":null,"Total":0}
引用次数: 0

摘要

在过去的几十年中,如果将超声波检查作为常规床旁检查的一部分,那么超声波检查并没有被证明是一种首选的检查方法。原因是人们认为超声波无法穿透肺部和骨骼结构。直到最近几年,在临床日常工作中使用这种工具的方法才发生了巨大变化,提供了所谓的床旁超声检查(POCUS)。纵向和横向伪影都成为有关病人临床状况的宝贵信息来源,从而帮助医生对病人进行鉴别诊断和监测。重要的是,这些信息都是实时提供的,而且操作本身也是非侵入性的。下一阶段,以机器学习算法为基础的人工智能(AI)的发展将标志着成像诊断领域的进步。本文旨在介绍超声系统现有的创新解决方案,包括智能 B 线技术,以确保自动识别过程以及对受检患者特定肺部区域的 B 线进行解读。文章总结了超声伪影和人工智能在 POCUS 中的应用现状。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Overview of artificial intelligence in point-of-care ultrasound. New horizons for respiratory system diagnoses.

Throughout the past decades ultrasonography did not prove to be a procedure of choice if regarded as part of the routine bedside examination. The reason was the assumption defining the lungs and the bone structures as impenetrable by ultrasound. Only during the recent several years has the approach to the use of such tool in clinical daily routines changed dramatically to offer so-called point-of-care ultrasonography (POCUS). Both vertical and horizontal artefacts became valuable sources of information about the patient's clinical condition, assisting therefore the medical practitioner in differential diagnosis and monitoring of the patient. What is important is that the information is delivered in real time, and the procedure itself is non-invasive. The next stage marking the progress made in this area of diagnostic imaging is the development of arti-ficial intelligence (AI) based on machine learning algorithms. This article is intended to present the available, innovative solutions of the ultrasound systems, including Smart B-line technology, to ensure automatic identification process, as well as interpretation of B-lines in the given lung area of the examined patient. The article sums up the state of the art in ultrasound artefacts and AI applied in POCUS.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
3.00
自引率
5.90%
发文量
48
审稿时长
25 weeks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信