ArticleIndian journal of anaesthesia2025
Role of artificial intelligence in enhancing mechanical ventilation - A peek into the future.
Article in Indian journal of anaesthesia, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed.
- Artificial intelligence in emergency mechanical ventilation: a prospective observational comparison with emergency physician ventilator settings.BMC emergency medicine · 2026Observational
- Mirror, mirror on the wall, can artificial intelligence predict it all?Indian journal of anaesthesia · 2026Article
- Continuous non-invasive measurement of tidal volume and minute ventilation using a smart nasal cannula.Critical care (London, England) · 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.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This article explores recent advancements in the role of artificial intelligence (AI) in enhancing mechanical ventilation (MV), accentuating its potential to mitigate risks such as ventilator-induced lung injury, ventilator-associated pneumonia and asynchronies. The integration of AI, including machine learning, natural language processing and predictive analytics, into MV is reshaping the landscape of critical care, offering advanced solutions to enhance patient outcomes with real-time monitoring, personalised ventilation strategies, early detection of complications and also increased operational efficiency. Key practical issues surrounding the implementation of AI into existing clinical workflows, including data quality, data sharing and privacy, data standardisation, seamless integration with existing healthcare systems, transparency of algorithms, interoperability across multiple platforms, patient safety and addressing ethical concerns, remain. As we advance, a collaborative approach between AI and healthcare professionals will be essential to ensure optimal patient safety.
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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.