ArticleIndian journal of anaesthesia2024
Scope of artificial intelligence in airway management.
Article in Indian journal of anaesthesia, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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
10 citing papers in PubMed, 1 synthesis or guideline pooled it, 12 citations in OpenAlex.
- Pooled it
- AI-assisted videolaryngoscopy improves intubation success: results from a randomized simulation trial.Journal of clinical monitoring and computing · 2026Trial
- Artificial Intelligence in Airway Management: Current Evidence and Future Perspectives.Cureus · 2026Review
- Mirror, mirror on the wall, can artificial intelligence predict it all?Indian journal of anaesthesia · 2026Article
- Specialised Competencies and Artificial Intelligence in Perioperative Care: Contributions Toward Safer Practice.Healthcare (Basel, Switzerland) · 2025Review
- Human Factors in Airway Management: Designing Systems for Safer, Team-Based Care.Journal of clinical medicine · 2025Review
- Indian Journal of Anaesthesia Infographics of published articles.Indian journal of anaesthesia · 2025Article
- Emerging technologies in airway management: a narrative review of intubation robotics and anatomical structure recognition algorithms.Biomedical engineering online · 2025Review
- Tracheostomy in the Digital Age: How Artificial Intelligence and Immersive Technologies Are Redefining Airway Care.Tracheostomy (Warrenville, Ill.) · 2025Article
- Reshaping Anesthesia with Artificial Intelligence: From Concept to Reality.Anesthesia and critical care (Houston, Tex.) · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The evolution of artificial intelligence (AI) systems in the field of anaesthesiology owes to notable advancements in data processing, databases, algorithmic programs, and computation power. Over the past decades, its accelerated progression has enhanced safety in anaesthesia by improving the efficiency of equipment, perioperative risk assessments, monitoring, and drug administration systems. AI in the field of anaesthesia aims to improve patient safety, optimise resources, and improve the quality of anaesthesia management in all phases of perioperative care. The use of AI is likely to impact difficult airway management and patient safety considerably. AI has been explored to predict difficult intubation to outperform conventional airway examinations by integrating subjective factors, such as facial appearance, speech features, habitus, and other poorly known features. This narrative review delves into the status of AI in airway management, the most recent developments in this field, and its future clinical applications.
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.