ArticleAnnals of thoracic medicine
Artificial intelligence in respiratory care: Current scenario and future perspective.
Article in Annals of thoracic medicine. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers, 1 of them a synthesis that pooled it.
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
38 citing papers in PubMed, 1 synthesis or guideline pooled it.
- High-flow nasal cannula for acute respiratory failure: a bibliometric analysis of current trends and future directions.Frontiers in medicine · 2026Pooled it
- Geriatric respiratory medicine 2026: from artificial intelligence to personalised management of the multimorbid patient.European respiratory review : an official journal of the European Respiratory Society · 2026Review
- Advanced Pulmonary Drug Delivery Systems: A Narrative Review.Pulmonary therapy · 2026Review
- Artificial Intelligence-Related Risks in Interventional Pulmonology: An Exploratory Enumeration and Ranking Study Across Five General-Purpose Large Language Models.Journal of clinical medicine · 2026Article
- Applications of artificial intelligence in dyspnoea management for patients with advanced lung cancer: a scoping review protocol.BMJ open · 2026Article
- Systematic review of artificial intelligence and digital-automated tools for screening, diagnosis and characterisation of primary ciliary dyskinesia.ERJ open research · 2026Article
- Current Clinical Perspectives of Biomarkers in Respiratory Diseases: A Narrative Review.Journal of clinical medicine · 2026Review
- Artificial Intelligence-Induced Deskilling in Interventional Pulmonology: An International Cross-Sectional Survey on Risk Perception and Mitigation Strategies.Advances in respiratory medicine · 2026Observational
- Pulmonary Drug Delivery in the Era of Nanomedicine: From Biological Barriers to Artificial Intelligence-Driven Optimization.Pharmaceuticals (Basel, Switzerland) · 2026Review
- Artificial Intelligence and Endobronchial Ultrasound for Lymph-Node Detection and Characterization: A Pioneer Multicenter Transatlantic Study.Journal of clinical medicine · 2026Article
- Artificial intelligence in respiratory medicine: From diagnosis to treatment and future directions.Chinese medical journal pulmonary and critical care medicine · 2026Review
- Artificial intelligence in emergency mechanical ventilation: a prospective observational comparison with emergency physician ventilator settings.BMC emergency medicine · 2026Observational
- Artificial intelligence and radiomics in drug-induced interstitial lung disease.ERJ open research · 2026Review
- Idiopathic pulmonary fibrosis from a multiscale mechanobiology perspective: Mechanisms and future therapeutic prospects.iScience · 2026Review
- Artificial Intelligence in Pulmonary Endoscopy: Current Evidence, Limitations, and Future Directions.Journal of imaging · 2026Review
- The price of immune awakening: bridging knowledge gaps in checkpoint inhibitor-related pneumonitis in lung cancer.Breathe (Sheffield, England) · 2026Article
- Artificial intelligence for pleural effusion and pneumothorax detection on thoracic ultrasound: an educational viewpoint on the promise, pitfalls and path forward.Breathe (Sheffield, England) · 2026Article
- New Personalized Medicine Model for Medication Management.Journal of personalized medicine · 2026Review
- Ethical, legal, and social issues of AI use in emergency healthcare: a scoping review.BMC medical informatics and decision making · 2026Article
- Artificial Intelligence-Based Automated Analysis for Pleural Effusion Detection on Thoracic Ultrasound: A Systematic Review.Diagnostics (Basel, Switzerland) · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThis narrative review aims to explore the current state and future perspective of artificial intelligence (AI) in respiratory care. The objective is to provide insights into the potential impact of AI in this field.
methodsA comprehensive analysis of relevant literature and research studies was conducted to examine the applications of AI in respiratory care and identify areas of advancement. The analysis included studies on remote monitoring, early detection, smart ventilation systems, and collaborative decision-making.
resultsThe obtained results highlight the transformative potential of AI in respiratory care. AI algorithms have shown promising capabilities in enabling tailored treatment plans based on patient-specific data. Remote monitoring using AI-powered devices allows for real-time feedback to health-care providers, enhancing patient care. AI algorithms have also demonstrated the ability to detect respiratory conditions at an early stage, leading to timely interventions and improved outcomes. Moreover, AI can optimize mechanical ventilation through continuous monitoring, enhancing patient comfort and reducing complications. Collaborative AI systems have the potential to augment the expertise of health-care professionals, leading to more accurate diagnoses and effective treatment strategies.
conclusionBy improving diagnosis, AI has the potential to revolutionize respiratory care, treatment planning, and patient monitoring. While challenges and ethical considerations remain, the transformative impact of AI in this domain cannot be overstated. By leveraging the advancements and insights from this narrative review, health-care professionals and researchers can continue to harness the power of AI to improve patient outcomes and enhance respiratory care practices. IMPROVEMENTS: Based on the findings, future research should focus on refining AI algorithms to enhance their accuracy, reliability, and interpretability. In addition, attention should be given to addressing ethical considerations, ensuring data privacy, and establishing regulatory frameworks to govern the responsible implementation of AI in respiratory care.
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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.