{"title":"利用基于人工智能的工具处理临床查询:ChatGPT Versus Google Gemini.","authors":"Leodoro J Labrague","doi":"10.3928/01484834-20240426-01","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Artificial intelligence (AI)-based text generators, such as ChatGPT (OpenAI) and Google Bard (now Google Gemini), have demonstrated proficiency in predicting words and providing responses to various questions. However, their performance in answering clinical queries has not been well assessed. This comparative analysis aimed to assess the capabilities of ChatGPT and Google Gemini in addressing clinical questions.</p><p><strong>Method: </strong>Separate interactions with ChatGPT and Google Gemini were conducted to obtain responses to the clinical question, posed in a PICOT (patient, intervention, comparison, outcome, time) format. To ascertain the accuracy of the information provided by the AI chat bots, a thorough examination of full-text articles was conducted.</p><p><strong>Results: </strong>Although ChatGPT exhibited relative accuracy in generating bibliographic information, it displayed some inconsistencies in clinical content. Conversely, Google Gemini generated citations and summaries that were entirely fabricated.</p><p><strong>Conclusion: </strong>Despite generating responses that may appear credible, both AI-based tools exhibited factual inaccuracies, raising substantial concerns about their reliability as potential sources of clinical information. <b>[<i>J Nurs Educ</i>. 2024;63(8):556-559.]</b>.</p>","PeriodicalId":94241,"journal":{"name":"The Journal of nursing education","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Utilizing Artificial Intelligence-Based Tools for Addressing Clinical Queries: ChatGPT Versus Google Gemini.\",\"authors\":\"Leodoro J Labrague\",\"doi\":\"10.3928/01484834-20240426-01\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Artificial intelligence (AI)-based text generators, such as ChatGPT (OpenAI) and Google Bard (now Google Gemini), have demonstrated proficiency in predicting words and providing responses to various questions. However, their performance in answering clinical queries has not been well assessed. This comparative analysis aimed to assess the capabilities of ChatGPT and Google Gemini in addressing clinical questions.</p><p><strong>Method: </strong>Separate interactions with ChatGPT and Google Gemini were conducted to obtain responses to the clinical question, posed in a PICOT (patient, intervention, comparison, outcome, time) format. To ascertain the accuracy of the information provided by the AI chat bots, a thorough examination of full-text articles was conducted.</p><p><strong>Results: </strong>Although ChatGPT exhibited relative accuracy in generating bibliographic information, it displayed some inconsistencies in clinical content. Conversely, Google Gemini generated citations and summaries that were entirely fabricated.</p><p><strong>Conclusion: </strong>Despite generating responses that may appear credible, both AI-based tools exhibited factual inaccuracies, raising substantial concerns about their reliability as potential sources of clinical information. <b>[<i>J Nurs Educ</i>. 2024;63(8):556-559.]</b>.</p>\",\"PeriodicalId\":94241,\"journal\":{\"name\":\"The Journal of nursing education\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"The Journal of nursing education\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3928/01484834-20240426-01\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Journal of nursing education","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3928/01484834-20240426-01","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
背景:基于人工智能(AI)的文本生成器,如 ChatGPT(OpenAI)和 Google Bard(现为 Google Gemini),已经在预测单词和回答各种问题方面表现出了一定的能力。但是,它们在回答临床询问方面的性能还没有得到很好的评估。本对比分析旨在评估 ChatGPT 和谷歌双子星在解决临床问题方面的能力:方法:分别与 ChatGPT 和 Google Gemini 进行交互,以获得对临床问题的回复,回复以 PICOT(患者、干预、比较、结果、时间)格式提出。为了确定人工智能聊天机器人所提供信息的准确性,对全文文章进行了全面检查:结果:虽然 ChatGPT 在生成文献信息方面表现出了相对的准确性,但在临床内容方面却显示出了一些不一致性。相反,谷歌双子座生成的引文和摘要完全是编造的:结论:尽管这两种基于人工智能的工具生成的回复看似可信,但它们都显示出与事实不符的地方,这让人对它们作为潜在临床信息来源的可靠性产生了极大的担忧。[护理教育杂志,2024;63(8):556-559]。
Utilizing Artificial Intelligence-Based Tools for Addressing Clinical Queries: ChatGPT Versus Google Gemini.
Background: Artificial intelligence (AI)-based text generators, such as ChatGPT (OpenAI) and Google Bard (now Google Gemini), have demonstrated proficiency in predicting words and providing responses to various questions. However, their performance in answering clinical queries has not been well assessed. This comparative analysis aimed to assess the capabilities of ChatGPT and Google Gemini in addressing clinical questions.
Method: Separate interactions with ChatGPT and Google Gemini were conducted to obtain responses to the clinical question, posed in a PICOT (patient, intervention, comparison, outcome, time) format. To ascertain the accuracy of the information provided by the AI chat bots, a thorough examination of full-text articles was conducted.
Results: Although ChatGPT exhibited relative accuracy in generating bibliographic information, it displayed some inconsistencies in clinical content. Conversely, Google Gemini generated citations and summaries that were entirely fabricated.
Conclusion: Despite generating responses that may appear credible, both AI-based tools exhibited factual inaccuracies, raising substantial concerns about their reliability as potential sources of clinical information. [J Nurs Educ. 2024;63(8):556-559.].