ReviewSaudi journal of anaesthesia
Artificial intelligence and anesthesia: A narrative review.
Review in Saudi journal of anaesthesia. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.
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
23 citing papers in PubMed, 1 synthesis or guideline pooled it, 79 citations in OpenAlex.
- Artificial intelligence and its clinical application in Anesthesiology: a systematic review.Journal of clinical monitoring and computing · 2024Pooled it
- From prediction to practice: closing the translation gap in artificial intelligence for anesthesia.Journal of clinical monitoring and computing · 2026Review
- Article
- Artificial Intelligence as a Support Tool for Preoperative Patient Education in Anesthesiology: A Comparative Evaluation of Five Large Language Models.Journal of clinical medicine · 2026Article
- Anesthesia for cesarean delivery in the era of artificial intelligence: a narrative review.Journal of anesthesia, analgesia and critical care · 2026Review
- Performance of Large Language Models in Complex Anesthesia Decision-Making: A Comparative Study of Four LLMs in High-Risk Patients.Journal of medical systems · 2025Article
- Comparison of AI applications and anesthesiologist's anesthesia method choices.BMC anesthesiology · 2025Article
- Reshaping Anesthesia with Artificial Intelligence: From Concept to Reality.Anesthesia and critical care (Houston, Tex.) · 2025Article
- AI-based hardware and software tools in microscopy to boost research in immunology and virology.Frontiers in immunology · 2025Review
- Artificial intelligence and robotics in regional anesthesia.World journal of methodology · 2024Article
- Review
- Regional Anaesthesia, Contemporary Techniques, and Associated Advancements: A Narrative Review.Cureus · 2024Review
- Intelligent algorithm based on deep learning to predict the dosage for anesthesia: A study on prediction of drug efficacy based on deep learning.Health science reports · 2024Article
- Attitudes of Jordanian Anesthesiologists and Anesthesia Residents towards Artificial Intelligence: A Cross-Sectional Study.Journal of personalized medicine · 2024Article
- Anesthesia decision analysis using a cloud-based big data platform.European journal of medical research · 2024Review
- Strengths-weaknesses-opportunities-threats analysis of artificial intelligence in anesthesiology and perioperative medicine.Frontiers in digital health · 2024Review
- Revolutionizing Patient Care: A Comprehensive Review of Artificial Intelligence Applications in Anesthesia.Cureus · 2023Review
- Recent advances in system management, decision support systems, artificial intelligence and computing in anaesthesia.Indian journal of anaesthesia · 2023Article
- Closed-Loop Controlled Fluid Administration Systems: A Comprehensive Scoping Review.Journal of personalized medicine · 2022Article
- The Use of Artificial Intelligence for Orthopedic Surgical Backlogs Such as the One Following the COVID-19 Pandemic: A Narrative Review.JB & JS open accessReview
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 at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Rapid advances in Artificial Intelligence (AI) have led to diagnostic, therapeutic, and intervention-based applications in the field of medicine. Today, there is a deep chasm between AI-based research articles and their translation to clinical anesthesia, which needs to be addressed. Machine learning (ML), the most widely applied arm of AI in medicine, confers the ability to analyze large volumes of data, find associations, and predict outcomes with ongoing learning by the computer. It involves algorithm creation, testing and analyses with the ability to perform cognitive functions including association between variables, pattern recognition, and prediction of outcomes. AI-supported closed loops have been designed for pharmacological maintenance of anesthesia and hemodynamic management. Mechanical robots can perform dexterity and skill-based tasks such as intubation and regional blocks with precision, whereas clinical-decision support systems in crisis situations may augment the role of the clinician. The possibilities are boundless, yet widespread adoption of AI is still far from the ground reality. Patient-related "Big Data" collection, validation, transfer, and testing are under ethical scrutiny. For this narrative review, we conducted a PubMed search in 2020-21 and retrieved articles related to AI and anesthesia. After careful consideration of the content, we prepared the review to highlight the growing importance of AI in anesthesia. Awareness and understanding of the basics of AI are the first steps to be undertaken by clinicians. In this narrative review, we have discussed salient features of ongoing AI research related to anesthesia and perioperative care.
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.