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Artificial intelligence in anesthesiology: a bibliometric analysis.

Bi-Hua Xie1,2, Ting-Ting Li1, Feng-Ting Ma1,3

  • 1Department of Anesthesiology, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, China.

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Summary
This summary is machine-generated.

Artificial intelligence (AI) in anesthesiology is growing rapidly. This bibliometric analysis reveals key research trends, top contributors, and emerging areas like AI for predicting hypotension.

Keywords:
Airway managementAnesthesiologyArtificial intelligenceClosed-loop infusionDepth of anesthesiaPostoperative painPredictUltrasound-guided regional anesthesia

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Area of Science:

  • Anesthesiology
  • Artificial Intelligence
  • Bibliometrics

Background:

  • Artificial intelligence (AI) applications are expanding in anesthesiology.
  • Previous bibliometric analyses of this specific field are lacking.
  • Understanding global research trends is crucial for future development.

Purpose of the Study:

  • To conduct a bibliometric analysis of global research trends in AI in anesthesiology.
  • To identify key countries, institutions, authors, and journals.
  • To map the research landscape and identify hotspots and frontiers.

Main Methods:

  • Bibliometric analysis of 491 studies retrieved from Web of Science until April 10, 2024.
  • Data visualization and analysis using Excel, CiteSpace, and VOSviewer.
  • Computation of publication growth, country/institution/author/journal contributions, co-citations, and keyword co-occurrences.

Main Results:

  • Publication numbers have increased annually since 2018.
  • The USA, China, and England are leading contributors.
  • Research on AI for predicting hypotension is a significant hotspot.
  • Key research clusters include ultrasound-guided regional anesthesia, pain management, and intraoperative drug infusion.

Conclusions:

  • This bibliometric analysis provides a comprehensive overview of AI research in anesthesiology.
  • It highlights the USA, China, and England as major contributors.
  • Emerging research frontiers include AI applications in predicting hypotension and optimizing intraoperative care.