ReviewWorld journal of otorhinolaryngology - head and neck surgery2026
The Use of Ambient Dictation Artificial Intelligence in Clinical Spaces in Surgery: A Scoping Review.
Review in World journal of otorhinolaryngology - head and neck surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: To determine the current scope of knowledge regarding ambient listening artificial intelligence (AI) tools for documentation in surgical clinical environments. Data Sources: Literature search was performed using EMBASE, PubMed (MEDLINE), CINAHL, SCOPUS, and Cochrane databases. Citation searching was utilized to identify additional studies. Methods: A scoping review regarding the use of ambient dictation artificial intelligence in clinical note generation in surgery was performed per PRISMA-ScR guidelines. Two reviewers independently performed title and abstract screening, full-text review, and data extraction. Inclusion criteria included studies describing the use of ambient listening AI tools for the generation of clinical documentation for surgery, with full-text available, in English or English-language translation. Results: Of 252 studies identified through database and citation searching, 12 met the inclusion criteria. Narrative reviews were most common ( Conclusion: Documentation burden is a common contributor to clinician burnout in the medical field. AI scribing technologies have the potential to promote clinic efficiency and decrease documentation burden. The current research landscape regarding the implementation of these tools in surgical specialties is sparse and warrants further primary research in the future.
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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.