ReviewKorean journal of anesthesiology2022
Artificial intelligence in perioperative medicine: a narrative review.
Review in Korean journal of anesthesiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07290647 (Prospective Validation of an Artificial Intelligence Tool for Pre-Anesthetic Assessment), which is not on this map. Cited by 19 papers.
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.
Prospective Validation of an Artificial Intelligence Tool for Pre-Anesthetic Assessment
Who cites it
19 citing papers in PubMed.
- AI Trustworthiness in the Perioperative Period for Patients with Serious Illness: Scoping Narrative Review.JMIR perioperative medicine · 2026Article
- Perioperative Risk Stratification with AI-Powered Chatbots: A Systematic Review and Meta-Analysis.Journal of clinical medicine · 2026Review
- Cohort profile: PeRiOperative sTress risk assEssment and Clinical decision cohorT (PROTECT), a multi-center observational study based on real-world data.BMC geriatrics · 2026Observational
- MRI-based extensor carpi ulnaris tendon cross-sectional area as a quantitative biomarker for extensor carpi ulnaris tenosynovitis.Frontiers in digital health · 2026Article
- From Data to Decisions: Harnessing Multi-Agent Systems for Safer, Smarter, and More Personalized Perioperative Care.Journal of personalized medicine · 2025Review
- Article
- Multicenter validation of a scalable, interpretable, multitask prediction model for multiple clinical outcomes.NPJ digital medicine · 2025Article
- From static to dynamic: Artificial intelligence revolution in perioperative care through multimodal data fusion and closed-loop optimization.Journal of anesthesia and translational medicine · 2025Review
- Wearable Technology in Surgery: New Developments Toward Real-Time Patient Monitoring.ANZ journal of surgery · 2025Article
- Blood transfusion in total knee arthroplasty and total hip arthroplasty: A nationwide study of complications, costs and predictive modelling.Journal of experimental orthopaedics · 2025Article
- Respiratory Depression in Non-Operating Room Anesthesia: An Overview.Journal of clinical medicine · 2025Review
- Reshaping Anesthesia with Artificial Intelligence: From Concept to Reality.Anesthesia and critical care (Houston, Tex.) · 2025Article
- Machine-learning model to predict the tacrolimus concentration and suggest optimal dose in liver transplantation recipients: a multicenter retrospective cohort study.Scientific reports · 2024Article
- Machine learning-based model development for predicting risk factors of prolonged intra-aortic balloon pump therapy in patients with coronary artery bypass grafting.Journal of cardiothoracic surgery · 2024Article
- Development of machine learning models to predict perioperative blood transfusion in hip surgery.BMC medical informatics and decision making · 2024Article
- Real-time machine learning model to predict short-term mortality in critically ill patients: development and international validation.Critical care (London, England) · 2024Article
- Open datasets in perioperative medicine: a narrative review.Anesthesia and pain medicine · 2023Review
- Artificial intelligence in surgery: the emergency surgeon's perspective (the ARIES project).Discover health systems · 2022Review
- Comparative evaluation of artificial intelligence chatbots for real-time guidance during intraoperative anesthetic crises: A simulation-based study.Saudi journal of anaesthesiaArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Recent advancements in artificial intelligence (AI) techniques have enabled the development of accurate prediction models using clinical big data. AI models for perioperative risk stratification, intraoperative event prediction, biosignal analyses, and intensive care medicine have been developed in the field of perioperative medicine. Some of these models have been validated using external datasets and randomized controlled trials. Once these models are implemented in electronic health record systems or software medical devices, they could help anesthesiologists improve clinical outcomes by accurately predicting complications and suggesting optimal treatment strategies in real-time. This review provides an overview of the AI techniques used in perioperative medicine and a summary of the studies that have been published using these techniques. Understanding these techniques will aid in their appropriate application in clinical practice.
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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.