Artificial intelligence in regional anesthesia

Emerging AI applications in UGRA warrant further study due to an opaque and fragmented evidence base. Robust and consistent evaluation and reporting of algorithm performance, in a representative clinical context, will expedite discovery and appropriate deployment of AI in UGRA. A clinician-focused approach to the development, evaluation, and implementation of this exciting branch of AI has huge potential to advance the human art of regional anesthesia.

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Publication Details

Journal
Current Opinion in Anaesthesiology
Published
2025-04-21
DOI
https://doi.org/10.1097/aco.0000000000001505
Citations
7
Primary Topic
Cardiac, Anesthesia and Surgical Outcomes
Type
article
Field-Weighted Citation Impact
9.72
Controls
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article

Artificial intelligence in regional anesthesia

Joseph Harris, Damon Kamming, James Simeon Bowness
7 citations
Current Opinion in Anaesthesiology
Cardiac, Anesthesia and Surgical Outcomes
9.72
article

Artificial intelligence in regional anesthesia

Joseph Harris, Damon Kamming, James Simeon Bowness
article en
7 citations

Abstract

Emerging AI applications in UGRA warrant further study due to an opaque and fragmented evidence base. Robust and consistent evaluation and reporting of algorithm performance, in a representative clinical context, will expedite discovery and appropriate deployment of AI in UGRA. A clinician-focused approach to the development, evaluation, and implementation of this exciting branch of AI has huge potential to advance the human art of regional anesthesia.

Current Opinion in AnaesthesiologyVol. 38(5)
University College London Hospitals NHS Foundation Trust (GB), University College London (GB)
Openalex Percentile: Top 2%
Cardiac, Anesthesia and Surgical Outcomes
9.72
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