ArticleBMC anesthesiology2025
Comparison of AI applications and anesthesiologist's anesthesia method choices.
Article in BMC anesthesiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Guideline-augmented prompting improves comparative preference and response consistency of large language model outputs for orthopaedic anaesthesia questions: A controlled prompting study.Journal of experimental orthopaedics · 2026Article
- Large Language Models in Perioperative Antithrombotic Management: A Blinded Scenario-Based Expert Evaluation.Diagnostics (Basel, Switzerland) · 2026Article
- Perioperative Risk Stratification with AI-Powered Chatbots: A Systematic Review and Meta-Analysis.Journal of clinical medicine · 2026Review
- 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
- The impact of regional block presence on large language model-based postoperative analgesia recommendations in abdominal surgery: a comparative study using real-world patient data.BMC anesthesiology · 2026Observational
- Artificial intelligence in anesthesiology education: transformative applications, challenges, and future perspectives.Frontiers in medicine · 2026Review
- Advancing a Hybrid Decision-Making Model in Anesthesiology: Applications of Artificial Intelligence in the Perioperative Setting.Healthcare (Basel, Switzerland) · 2025Review
- Artificial Intelligence in Anaesthesiology: Current Applications, Challenges, and Future Directions.Turkish journal of anaesthesiology and reanimation · 2025Article
- Reshaping Anesthesia with Artificial Intelligence: From Concept to Reality.Anesthesia and critical care (Houston, Tex.) · 2025Article
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Authors and funding
6 authors.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundIn medicine, Artificial intelligence has begun to be utilized in nearly every domain, from medical devices to the interpretation of imaging studies. There is still a need for more experience and more studies related to the comprehensive use of AI in medicine. The aim of the present study is to evaluate the ability of AI to make decisions regarding anesthesia methods and to compare the most popular AI programs from this perspective.
methodsThe study included orthopedic patients over 18 years of age scheduled for limb surgery within a 1-month period. Patients classified as ASA I-III who were evaluated in the anesthesia clinic during the preoperative period were included in the study. The anesthesia method preferred by the anesthesiologist during the operation and the patient's demographic data, comorbidities, medications, and surgical history were recorded. The obtained patient data were discussed as if presenting a patient scenario using the free versions of the ChatGPT, Copilot, and Gemini applications by a different anesthesiologist who did not perform the operation.
resultsOver the course of 1 month, a total of 72 patients were enrolled in the study. It was observed that both the anesthesia specialists and the Gemini application chose spinal anesthesia for the same patient in 68.5% of cases. This rate was higher compared to the other AI applications. For patients taking medication, it was observed that the Gemini application presented choices that were highly compatible (85.7%) with the anesthesiologists' preferences.
conclusionAI cannot fully master the guidelines and exceptional and specific cases that arrive in the course of medical treatment. Thus, we believe that AI can serve as a valuable assistant rather than replacing doctors.
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