An Exploratory Comparison of AI Models for Preoperative Anesthesia Planning: Assessing ChatGPT-4o, Claude 3.5 Sonnet, and ChatGPT-o1 in Clinical Scenario Analysis.

This exploratory study examined the effectiveness of ChatGPT-4o, Claude 3.5 Sonnet, and ChatGPT-o1 in developing anesthesia plans for critical cases. Personalized anesthesia plans are essential for ensuring surgical safety and patient satisfaction. These artificial intelligence (AI) models can under...

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Publicado en:Journal of Medical Systems Vol. 49; no. 1; pp. 1 - 11
Autores principales: Wang, Bing, Tian, Yue, Wang, Xue Ting
Formato: research tables/charts Journal Article
Publicado: Springer Nature 8/14/2025
Acceso en línea:Ver este registro en EBSCOhost
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      pub: Springer Nature
      place: New York, New York
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        atl: An Exploratory Comparison of AI Models for Preoperative Anesthesia Planning: Assessing ChatGPT-4o, Claude 3.5 Sonnet, and ChatGPT-o1 in Clinical Scenario Analysis.
      aug:
        au:
          Wang, Bing
          Tian, Yue
          Wang, Xue Ting
        affil: https://ror.org/032d4f246 Department of Anesthesiology, Fourth Hospital of China Medical University, Shenyang, China
      sug:
        subj:
          Preoperative Care Methods
          Anesthesia
          Artificial Intelligence, Generative
          Prediction Models
          Patient Satisfaction
          Patient Safety
          Human
          Multimethod Studies
          Decision Making, Clinical
          Postoperative Care
          Feedback
          Comorbidity
          Severity of Illness
          Data Analysis Software
          Kruskal-Wallis Test
          Post Hoc Analysis
          Descriptive Statistics
          Interrater Reliability
          Antiinflammatory Agents, Non-Steroidal
      ab: This exploratory study examined the effectiveness of ChatGPT-4o, Claude 3.5 Sonnet, and ChatGPT-o1 in developing anesthesia plans for critical cases. Personalized anesthesia plans are essential for ensuring surgical safety and patient satisfaction. These artificial intelligence (AI) models can understand and generate anesthesia-related information. The study included a panel of five anesthesia experts, each with over ten years of experience. They qualitatively and quantitatively assessed the capabilities of the three models in formulating anesthesia plans for critical cases. The results showed no significant differences in the response quality, relevance, and applicability scores among the models; however, variations were observed in the error types and severity. ChatGPT-o1 surpassed the other models in terms of content relevance and information accuracy, demonstrating a lower error rate and higher suitability for clinical application. As an initial investigation in this rapidly evolving field, this research provides preliminary insights while acknowledging the need for further validation in clinical settings before implementation.
      pubtype: Academic Journal
      doctype:
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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