Evidence map›Paper›PMID 39754097›Full record

ArticleBMC anesthesiology2025

Comparison of AI applications and anesthesiologist's anesthesia method choices.

Enes Çelik, Mehmet Ali Turgut, Mesut Aydoğan, Metin Kılınç, İzzettin Toktaş, Hakan Akelma

Abstract readComparative Study
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Observational
  6. Review
  7. Review
  8. Article
  9. Reshaping Anesthesia with Artificial Intelligence: From Concept to Reality.Anesthesia and critical care (Houston, Tex.) · 2025
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Enes ÇelikDepartment of Anesthesiology and Reanimation, Mardin Artuklu University School of Medicine, Diyarbakır Road, Artuklu, Mardin, 47100, Turkey. enescelik@artuklu.edu.tr.
Mehmet Ali TurgutMardin Training and Research Hospital, Anesthesia Clinic, Mardin, Turkey.
Mesut AydoğanPrivate Baglar Hospital, Anesthesia Clinic, Diyarbakir, Turkey.
Metin KılınçDepartment of Anesthesiology and Reanimation, Mardin Artuklu University School of Medicine, Diyarbakır Road, Artuklu, Mardin, 47100, Turkey.
İzzettin ToktaşDepartment of Public Health, Faculty of Medicine, Mardin Artuklu University, Mardin, Turkey.
Hakan AkelmaDepartment of Anesthesiology and Reanimation, Mardin Artuklu University School of Medicine, Diyarbakır Road, Artuklu, Mardin, 47100, Turkey.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

AnesthesiaAnesthesiologistsArtificial IntelligenceAdultAgedAnesthesia, SpinalFemaleHumansMaleMiddle AgedOrthopedic ProceduresAnesthesiaArtificial intelligenceMedical decision-makingPreoperative procedures

Identifiers

PMID39754097
PMCPMC11697632

What OpenQuestion holds

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Registered trials

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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.