ReviewHNO2022
[Artificial intelligence in otorhinolaryngology].
Review in HNO, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed.
- Beyond whole-image learning: anatomically partitioned deep learning models for superior sinonasal disease classification.European radiology · 2026Article
- Review
- Applications of Natural Language Processing in Otolaryngology: A Scoping Review.The Laryngoscope · 2025Article
- A Comprehensive Review of Diagnostic Approaches to Vocal Fold Paralysis Using Artificial Intelligence.Indian journal of otolaryngology and head and neck surgery : official publication of the Association of Otolaryngologists of India · 2025Article
- [Otorhinolaryngology is going digital].HNO · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe continued advancement of digitalization increasingly allows deployment of artificial intelligence (AI) algorithms, leveraging profound effects on society and medicine.
objectiveThis article aims to provide an overview of current developments and futures perspectives of AI in otorhinolaryngology. MATERIALS AND
methodsScientific studies and expert analyses were evaluated and discussed.
resultsAI can increase the value of current diagnostic tools in otorhinolaryngology and enhance surgical precision in head and neck surgery.
conclusionAI has the potential to further improve diagnostic and therapeutic procedures in otorhinolaryngology. This technology, however, is associated with challenges, for example in the domain of privacy and data security.
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.