{"title":"人工智能模型在术前麻醉计划中的探索性比较:评估chatgpt - 40、Claude 3.5 Sonnet和chatgpt - 01在临床场景分析中的应用","authors":"Bing Wang, Yue Tian, Xue Ting Wang","doi":"10.1007/s10916-025-02243-7","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":16338,"journal":{"name":"Journal of Medical Systems","volume":"49 1","pages":"104"},"PeriodicalIF":5.7000,"publicationDate":"2025-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An Exploratory Comparison of AI Models for Preoperative Anesthesia Planning: Assessing ChatGPT-4o, Claude 3.5 Sonnet, and ChatGPT-o1 in Clinical Scenario Analysis.\",\"authors\":\"Bing Wang, Yue Tian, Xue Ting Wang\",\"doi\":\"10.1007/s10916-025-02243-7\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>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.</p>\",\"PeriodicalId\":16338,\"journal\":{\"name\":\"Journal of Medical Systems\",\"volume\":\"49 1\",\"pages\":\"104\"},\"PeriodicalIF\":5.7000,\"publicationDate\":\"2025-08-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Medical Systems\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1007/s10916-025-02243-7\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"HEALTH CARE SCIENCES & SERVICES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Medical Systems","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s10916-025-02243-7","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
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 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.
期刊介绍:
Journal of Medical Systems provides a forum for the presentation and discussion of the increasingly extensive applications of new systems techniques and methods in hospital clinic and physician''s office administration; pathology radiology and pharmaceutical delivery systems; medical records storage and retrieval; and ancillary patient-support systems. The journal publishes informative articles essays and studies across the entire scale of medical systems from large hospital programs to novel small-scale medical services. Education is an integral part of this amalgamation of sciences and selected articles are published in this area. Since existing medical systems are constantly being modified to fit particular circumstances and to solve specific problems the journal includes a special section devoted to status reports on current installations.