eISSN: 1731-2531
ISSN: 1642-5758
Anaesthesiology Intensive Therapy
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1/2024
vol. 56
 
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abstract:
Review article

Overview of artificial intelligence in point-of-care ultrasound. New horizons for respiratory system diagnoses

Sławomir Mika
1
,
Wojciech Gola
2
,
Monika Gil-Mika
3
,
Mateusz Wilk
4
,
Hanna Misiołek
5

  1. Medica Co. Ltd. (Upper Silesian School of Ultrasonography), Poland
  2. Collegium Medicum, Jan Kochanowski University of Kielce, St. Luke Specialist Hospital in Końskie, Poland
  3. Municipal Hospital in Ruda Śląska Co. Ltd., Poland
  4. Collegium Medicum, WSB University, Dąbrowa Górnicza, Poland
  5. Department of Anaesthesiology and Critical Care, School of Medicine with the Division of Dentistry in Zabrze, Poland
Anaesthesiol Intensive Ther 2024; 56, 1: 1–8
Online publish date: 2024/03/29
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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 arti­ficial 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.
keywords:

lung ultrasound, artificial intelligence, point-of-care ultrasound, POCUS, Smart B-line, Auto B-line, B-lines

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