ReviewAnesthesia and pain medicine2025
Artificial intelligence in ultrasound-guided regional anesthesia: bridging the gap between potential and practice: a narrative review.
Review in Anesthesia and pain medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- The Role of Machine Learning and Artificial Intelligence in Enhancing Critical Care Nursing Practice: A Scoping Review.Nursing in critical care · 2026Article
- Current Status and Future Projections of Artificial Intelligence-Assisted Ultrasonography and Needle Visibility Methods in Regional Anesthesia.The Eurasian journal of medicine · 2026Article
- The impact of regional block presence on large language model-based postoperative analgesia recommendations in abdominal surgery: a comparative study using real-world patient data.BMC anesthesiology · 2026Observational
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Ultrasound-guided regional anesthesia (UGRA) offers substantial benefits in perioperative pain management; however, it remains underutilized because of technical complexity and training demands. Assistive artificial intelligence (AI) has emerged as a promising solution to support UGRA by enhancing anatomical recognition, procedural accuracy, and user confidence. This narrative review outlines the AI development pipeline for nerve visualization, describes available commercial tools, and summarizes clinical evidence. Although these technologies have the potential to democratize UGRA and reduce interoperator variability, limitations remain, including data bias, narrow anatomical coverage, and lack of outcome-based validation. Future efforts should focus on standardized evaluation, clinician-centered design, and rigorous clinical trials to ensure safe and effective integration of AI into UGRA practice.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.