医疗保健服务的ChatGPT:创新视角的新兴阶段

Mohd Javaid , Abid Haleem , Ravi Pratap Singh
{"title":"医疗保健服务的ChatGPT:创新视角的新兴阶段","authors":"Mohd Javaid ,&nbsp;Abid Haleem ,&nbsp;Ravi Pratap Singh","doi":"10.1016/j.tbench.2023.100105","DOIUrl":null,"url":null,"abstract":"<div><p>Generative Pretrained Transformer, often known as GPT, is an innovative kind of Artificial Intelligence (AI) which can produce writing that seems to have been written by a person. OpenAI created this AI language model called ChatGPT. It is built using the GPT architecture and is trained on a large corpus of text data to respond to natural language inquiries that resemble a person’s requirements. This technology has lots of applications in healthcare. The need for accurate and current data is one of the major obstacles to adopting ChatGPT in healthcare. GPT must have access to precise and up-to-date medical data to provide trustworthy suggestions and treatment options. It might be accomplished by ensuring that the data used by GPT is received from reliable sources and that the data is updated regularly. Since sensitive medical information would be involved, it will also be crucial to consider privacy and security issues while utilising GPT in the healthcare industry. This paper briefs about ChatGPT and its need for healthcare, its significant Work Flow Dimensions and typical features of ChatGPT for the Healthcare domain. Finally, it identified and discussed significant applications of ChatGPT for healthcare. ChatGPT can comprehend the conversational context and provide contextually appropriate replies. Its effectiveness as a conversational AI tool makes it useful for chatbots, virtual assistants, and other applications. However, we see many limitations in medical ethics, data interpretation, accountability and other issues related to the privacy. Regarding specialised tasks like text creation, language translation, text categorisation, text summarisation, and creating conversation systems, ChatGPT has been pre-trained on a large corpus of text data, and somewhat satisfactory results can be expected. Moreover, it can also be utilised for various Natural Language Processing (NLP) activities, including sentiment analysis, part-of-speech tagging, and named entity identification.</p></div>","PeriodicalId":100155,"journal":{"name":"BenchCouncil Transactions on Benchmarks, Standards and Evaluations","volume":"3 1","pages":"Article 100105"},"PeriodicalIF":0.0000,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"52","resultStr":"{\"title\":\"ChatGPT for healthcare services: An emerging stage for an innovative perspective\",\"authors\":\"Mohd Javaid ,&nbsp;Abid Haleem ,&nbsp;Ravi Pratap Singh\",\"doi\":\"10.1016/j.tbench.2023.100105\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Generative Pretrained Transformer, often known as GPT, is an innovative kind of Artificial Intelligence (AI) which can produce writing that seems to have been written by a person. OpenAI created this AI language model called ChatGPT. It is built using the GPT architecture and is trained on a large corpus of text data to respond to natural language inquiries that resemble a person’s requirements. This technology has lots of applications in healthcare. The need for accurate and current data is one of the major obstacles to adopting ChatGPT in healthcare. GPT must have access to precise and up-to-date medical data to provide trustworthy suggestions and treatment options. It might be accomplished by ensuring that the data used by GPT is received from reliable sources and that the data is updated regularly. Since sensitive medical information would be involved, it will also be crucial to consider privacy and security issues while utilising GPT in the healthcare industry. This paper briefs about ChatGPT and its need for healthcare, its significant Work Flow Dimensions and typical features of ChatGPT for the Healthcare domain. Finally, it identified and discussed significant applications of ChatGPT for healthcare. ChatGPT can comprehend the conversational context and provide contextually appropriate replies. Its effectiveness as a conversational AI tool makes it useful for chatbots, virtual assistants, and other applications. However, we see many limitations in medical ethics, data interpretation, accountability and other issues related to the privacy. Regarding specialised tasks like text creation, language translation, text categorisation, text summarisation, and creating conversation systems, ChatGPT has been pre-trained on a large corpus of text data, and somewhat satisfactory results can be expected. Moreover, it can also be utilised for various Natural Language Processing (NLP) activities, including sentiment analysis, part-of-speech tagging, and named entity identification.</p></div>\",\"PeriodicalId\":100155,\"journal\":{\"name\":\"BenchCouncil Transactions on Benchmarks, Standards and Evaluations\",\"volume\":\"3 1\",\"pages\":\"Article 100105\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"52\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"BenchCouncil Transactions on Benchmarks, Standards and Evaluations\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2772485923000224\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"BenchCouncil Transactions on Benchmarks, Standards and Evaluations","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2772485923000224","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 52

摘要

生成预训练转换器(Generative Pretrained Transformer),通常被称为GPT,是一种创新的人工智能(AI),它可以产生似乎是由个人编写的文字。OpenAI创建了一个名为ChatGPT的人工智能语言模型。它是使用GPT架构构建的,并在大型文本数据语料库上进行训练,以响应类似于个人需求的自然语言查询。这项技术在医疗保健领域有很多应用。对准确和最新数据的需求是在医疗保健中采用ChatGPT的主要障碍之一。GPT必须能够访问精确和最新的医疗数据,以提供值得信赖的建议和治疗选择。这可以通过确保GPT使用的数据是从可靠的来源接收的,并定期更新数据来实现。由于涉及敏感的医疗信息,在医疗保健行业使用GPT时,考虑隐私和安全问题也至关重要。本文简要介绍了ChatGPT及其对医疗保健的需求、其重要的工作流程维度以及ChatGPT在医疗保健领域的典型特征。最后,它确定并讨论了ChatGPT在医疗保健方面的重要应用。ChatGPT可以理解会话上下文并提供上下文适当的回复。它作为一种对话式人工智能工具的有效性使其对聊天机器人、虚拟助理和其他应用程序非常有用。然而,我们看到在医学伦理、数据解释、问责制和其他与隐私相关的问题上存在许多局限性。关于文本创建、语言翻译、文本分类、文本总结和创建对话系统等专业任务,ChatGPT已经在大量文本数据上进行了预训练,预计会取得一些令人满意的结果。此外,它还可以用于各种自然语言处理(NLP)活动,包括情感分析、词性标记和命名实体识别。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ChatGPT for healthcare services: An emerging stage for an innovative perspective

Generative Pretrained Transformer, often known as GPT, is an innovative kind of Artificial Intelligence (AI) which can produce writing that seems to have been written by a person. OpenAI created this AI language model called ChatGPT. It is built using the GPT architecture and is trained on a large corpus of text data to respond to natural language inquiries that resemble a person’s requirements. This technology has lots of applications in healthcare. The need for accurate and current data is one of the major obstacles to adopting ChatGPT in healthcare. GPT must have access to precise and up-to-date medical data to provide trustworthy suggestions and treatment options. It might be accomplished by ensuring that the data used by GPT is received from reliable sources and that the data is updated regularly. Since sensitive medical information would be involved, it will also be crucial to consider privacy and security issues while utilising GPT in the healthcare industry. This paper briefs about ChatGPT and its need for healthcare, its significant Work Flow Dimensions and typical features of ChatGPT for the Healthcare domain. Finally, it identified and discussed significant applications of ChatGPT for healthcare. ChatGPT can comprehend the conversational context and provide contextually appropriate replies. Its effectiveness as a conversational AI tool makes it useful for chatbots, virtual assistants, and other applications. However, we see many limitations in medical ethics, data interpretation, accountability and other issues related to the privacy. Regarding specialised tasks like text creation, language translation, text categorisation, text summarisation, and creating conversation systems, ChatGPT has been pre-trained on a large corpus of text data, and somewhat satisfactory results can be expected. Moreover, it can also be utilised for various Natural Language Processing (NLP) activities, including sentiment analysis, part-of-speech tagging, and named entity identification.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
4.80
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信