| Sumario: | 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.
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