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This summary is machine-generated.

Artificial intelligence (AI) enhances point-of-care ultrasound (POCUS) in critical care by improving image acquisition and interpretation. AI tools aim to broaden POCUS accessibility for clinicians of all skill levels.

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Area of Science:

  • Critical care medicine
  • Medical imaging
  • Artificial intelligence

Background:

  • Point-of-care ultrasound (POCUS) is vital in critical care.
  • Integration of artificial intelligence (AI) is enhancing POCUS capabilities.
  • AI offers potential for improved image quality and interpretation assistance.

Purpose of the Study:

  • To review current artificial intelligence (AI) applications in point-of-care ultrasound (POCUS).
  • To explore AI's role in image acquisition, interpretation, education, automation, guidance, and quality assurance.
  • To provide intensivists with insights into AI's current and future impact on POCUS.

Main Methods:

  • Narrative review of relevant studies on AI in POCUS.
  • Focus on key application domains within critical care settings.
  • Analysis of clinical utility, challenges, and future developments.

Main Results:

  • AI tools demonstrate potential to improve POCUS image quality and interpretation.
  • AI can provide real-time feedback and procedural guidance.
  • AI may democratize POCUS use across different operator expertise levels.

Conclusions:

  • AI is a transformative technology for point-of-care ultrasound (POCUS) in critical care.
  • Further development and integration of AI will enhance POCUS utility and accessibility.
  • Intensivists can leverage AI for improved patient care through advanced POCUS applications.