ReviewCureus2023
Revolutionizing Patient Care: A Comprehensive Review of Artificial Intelligence Applications in Anesthesia.
Review in Cureus, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 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
17 citing papers in PubMed, 33 citations in OpenAlex.
- Advances in Remote Monitoring Technology Applications in Anesthesia: A Narrative Review.Medical science monitor : international medical journal of experimental and clinical research · 2026Review
- Artificial Intelligence in Airway Management: Current Evidence and Future Perspectives.Cureus · 2026Review
- Evaluation of the accuracy, quality, and readability of large language models on local anesthesia and general anesthesia-sedation in dentistry.BMC anesthesiology · 2026Article
- Clinical Application of Artificial Intelligence in Anesthesiology: A Multicenter Retrospective Comparison Between Human Anesthetic Decisions and Algorithmic Recommendations in Non-Cardiac Surgery.Journal of personalized medicine · 2026Article
- A comparison of large language model-generated and published perioperative neurocognitive disorder recommendations: a cross-sectional web-based analysis.British journal of anaesthesia · 2026Article
- Artificial Intelligence and Robotics in Minimally Invasive and Complex Surgical Procedures: A Systematic Review.Cureus · 2025Review
- Reshaping Anesthesia with Artificial Intelligence: From Concept to Reality.Anesthesia and critical care (Houston, Tex.) · 2025Article
- Elevating surgical outcomes: a comprehensive analysis of innovative nursing practices in intraoperative care across diverse specialties.Frontiers in medicine · 2025Review
- AI-driven predictive modelling of orthodontic relapse using retainer compliance and patient factors.Bioinformation · 2025Article
- Indonesian Patients' Experiences and Emotional Attachment to Healthcare Services Abroad: A Qualitative Study.Patient preference and adherence · 2025Article
- A review of recent advances in anesthetic drugs for patients undergoing cardiac surgery.Frontiers in pharmacology · 2025Review
- Recent Advances and Perspectives in Anesthesiology: Towards Artificial Intelligence-Based Applications.Journal of clinical medicine · 2024Article
- Review
- Revolutionizing Cardiac Anesthesia: A Comprehensive Review of Contemporary Approaches Outside the Operating Room.Cureus · 2024Review
- Scope of artificial intelligence in airway management.Indian journal of anaesthesia · 2024Article
- Article
- Bridging neural circuits and clinical outcomes: a novel framework for perioperative disturbances of consciousness and cognition.Frontiers in neurologyReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This review explores the intersection of artificial intelligence (AI) and anesthesia, examining its transformative impact on patient care across various phases. Beginning with a historical overview of anesthesia, we highlight the critical role of technological advancements in ensuring optimal patient outcomes. The emergence of AI in healthcare sets the stage for a comprehensive analysis of its applications in anesthesia. In the preoperative phase, AI facilitates personalized risk assessments and decision support, optimizing anesthesia planning and drug dosage predictions. Moving to the intraoperative phase, we delve into AI's role in monitoring and control through sophisticated anesthesia monitoring and closed-loop systems. Additionally, we discuss the integration of robotics and AI-guided procedures, revolutionizing surgical assistance. Transitioning to the postoperative phase, we explore AI-driven postoperative monitoring, predictive analysis for complications, and the integration of AI into rehabilitation programs and long-term follow-up. These new applications redefine patient recovery, emphasizing personalized care and proactive interventions. However, the integration of AI in anesthesia poses challenges and ethical considerations. Data security, interpretability, and bias in AI algorithms demand scrutiny. Moreover, the evolving patient-doctor relationship in an AI-driven care landscape requires a delicate balance between efficiency and human touch. Looking forward, we discuss the future directions of AI in anesthesia, anticipating advances in technology and AI algorithms. The integration of AI into routine clinical practice and its potential impact on anesthesia education and training are explored, emphasizing the need for collaboration, education, and ethical guidelines. This review provides a comprehensive overview of AI applications in anesthesia, offering insights into the present landscape, challenges, and future directions. The synthesis of historical perspectives, current applications, and future possibilities underscores the transformative potential of AI in revolutionizing patient care within the dynamic field of anesthesia.
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.