ArticleTracheostomy (Warrenville, Ill.)2025
Tracheostomy in the Digital Age: How Artificial Intelligence and Immersive Technologies Are Redefining Airway Care.
Article in Tracheostomy (Warrenville, Ill.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Advancing Equity in Tracheostomy Care with the Individuals with Disabilities Education Act.Tracheostomy (Warrenville, Ill.) · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Tracheostomy care is a critical aspect of airway management, yet persistent gaps in provider training, patient education, and healthcare accessibility contribute to inconsistent clinical outcomes. Innovative technologies offer the promise of accelerated learning and scalable interventions. Artificial intelligence (AI), simulation, and digital health solutions have transformative potential for bridging these deficiencies. This article explores the integration of AI-driven technologies in tracheostomy education, workforce development, telehealth, predictive analytics, and robotic-assisted airway management. AI-powered learning platforms, including virtual reality simulations and conversational AI, enhance skill acquisition and clinical confidence, addressing significant competency deficits. Telehealth solutions, augmented by AI-driven monitoring and decision-support systems, can improve follow-up care, reduce hospitalizations, and expand patient access to expert consultation. Additionally, predictive analytics and machine learning models can optimize tracheostomy placement, complication prevention, and long-term patient outcomes, while robotic-assisted airway interventions demonstrate potential for enhanced procedural precision. Despite these advancements, challenges such as algorithm transparency, content readability, and human oversight must be addressed to maximize AI's effectiveness. As AI continues to evolve, future research should focus on refining these technologies, ensuring ethical implementation, and integrating AI solutions into standardized clinical workflows to enhance patient safety and healthcare efficiency.
Indexed as
Identifiers
What Socratic 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 Socratic graph.