ReviewMedical gas research2027
Hyperbaric oxygen in the artificial intelligence era: integration and innovation.
Review in Medical gas research, 2027. 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
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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
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Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Hyperbaric oxygen therapy is established for decompression illness, carbon monoxide poisoning, radiation-induced tissue injury, and diabetic foot ulcers. Interest in neurological and inflammatory indications is growing, yet outcomes are constrained by heterogeneous protocols, limited patient selection tools, and the absence of real-time physiological guidance. Artificial intelligence, including machine learning, explainable artificial intelligence, and digital twins, has transformed other clinical domains and could enable precision hyperbaric oxygen therapy. We searched PubMed, Scopus, Web of Science, and Google Scholar (January 2000-March 2025). Terms included "hyperbaric oxygen therapy" and ("artificial intelligence" OR "machine learning" OR "deep learning" OR "digital twin" OR "biosensor*"). English-language, peer-reviewed clinical, preclinical, or computational studies explicitly linking hyperbaric oxygen therapy with artificial intelligence or enabling technologies were eligible. Editorials without primary data, abstracts without full text, and non-peer-reviewed sources were excluded. A Preferred Reporting Items for Systematic Reviews and Meta-Analyses-style flow-guided screening and selection. Fifty-three eligible studies (≥30% from 2022-2025) illustrate four convergent application areas: (1) protocol optimization using multicenter data, (2) biomarker-driven patient selection via multi-omics and imaging, (3) real-time adaptive control using biosensors, and (4) predictive safety analytics for oxygen toxicity and barotrauma. Exemplars from radiology, critical care, and cardiology demonstrate the feasibility of decision support, federated learning, and digital-twin simulations adaptable to hyperbaric oxygen therapy. Integrating artificial intelligence with hyperbaric oxygen therapy can shift practice from empirical protocols to patient-tailored, data-informed therapy. Priorities include hybrid clinical trials, interoperable registries, explainable and bias-aware models, and regulatory-aligned validation. With rigorous governance, artificial intelligence can improve efficacy, safety, and efficiency while advancing mechanistic understanding of hyperbaric oxygen therapy.
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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.