{"title":"在病理学中使用 ChatGPT 可能带来的益处、挑战、隐患和未来展望","authors":"Durre Aden , Sufian Zaheer , Sabina Khan","doi":"10.1016/j.patol.2024.04.003","DOIUrl":null,"url":null,"abstract":"<div><p>The much-hyped artificial intelligence (AI) model called ChatGPT developed by Open AI can have great benefits for physicians, especially pathologists, by saving time so that they can use their time for more significant work. Generative AI is a special class of AI model, which uses patterns and structures learned from existing data and can create new data. Utilizing ChatGPT in Pathology offers a multitude of benefits, encompassing the summarization of patient records and its promising prospects in Digital Pathology, as well as its valuable contributions to education and research in this field. However, certain roadblocks need to be dealt like integrating ChatGPT with image analysis which will act as a revolution in the field of pathology by increasing diagnostic accuracy and precision. The challenges with the use of ChatGPT encompass biases from its training data, the need for ample input data, potential risks related to bias and transparency, and the potential adverse outcomes arising from inaccurate content generation. Generation of meaningful insights from the textual information which will be efficient in processing different types of image data, such as medical images, and pathology slides. Due consideration should be given to ethical and legal issues including bias.</p></div>","PeriodicalId":39194,"journal":{"name":"Revista Espanola de Patologia","volume":"57 3","pages":"Pages 198-210"},"PeriodicalIF":0.0000,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Possible benefits, challenges, pitfalls, and future perspective of using ChatGPT in pathology\",\"authors\":\"Durre Aden , Sufian Zaheer , Sabina Khan\",\"doi\":\"10.1016/j.patol.2024.04.003\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>The much-hyped artificial intelligence (AI) model called ChatGPT developed by Open AI can have great benefits for physicians, especially pathologists, by saving time so that they can use their time for more significant work. Generative AI is a special class of AI model, which uses patterns and structures learned from existing data and can create new data. Utilizing ChatGPT in Pathology offers a multitude of benefits, encompassing the summarization of patient records and its promising prospects in Digital Pathology, as well as its valuable contributions to education and research in this field. However, certain roadblocks need to be dealt like integrating ChatGPT with image analysis which will act as a revolution in the field of pathology by increasing diagnostic accuracy and precision. The challenges with the use of ChatGPT encompass biases from its training data, the need for ample input data, potential risks related to bias and transparency, and the potential adverse outcomes arising from inaccurate content generation. Generation of meaningful insights from the textual information which will be efficient in processing different types of image data, such as medical images, and pathology slides. Due consideration should be given to ethical and legal issues including bias.</p></div>\",\"PeriodicalId\":39194,\"journal\":{\"name\":\"Revista Espanola de Patologia\",\"volume\":\"57 3\",\"pages\":\"Pages 198-210\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Revista Espanola de Patologia\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1699885524000424\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"Medicine\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Revista Espanola de Patologia","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1699885524000424","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 0
摘要
Open AI 开发的名为 ChatGPT 的人工智能(AI)模型备受关注,它可以为医生(尤其是病理学家)节省时间,使他们可以把时间用在更重要的工作上,从而为他们带来巨大的益处。生成式人工智能是一种特殊的人工智能模型,它使用从现有数据中学到的模式和结构,并能创建新数据。在病理学领域使用 ChatGPT 有很多好处,包括病人记录的汇总、其在数字病理学领域的广阔前景以及对该领域教育和研究的宝贵贡献。然而,还需要解决一些障碍,比如将 ChatGPT 与图像分析相结合,这将提高诊断的准确性和精确度,从而成为病理学领域的一场革命。使用 ChatGPT 所面临的挑战包括其训练数据的偏差、对大量输入数据的需求、与偏差和透明度相关的潜在风险,以及因内容生成不准确而产生的潜在不良后果。从文本信息中生成有意义的见解,从而有效处理不同类型的图像数据,如医学图像和病理切片。应适当考虑道德和法律问题,包括偏见。
Possible benefits, challenges, pitfalls, and future perspective of using ChatGPT in pathology
The much-hyped artificial intelligence (AI) model called ChatGPT developed by Open AI can have great benefits for physicians, especially pathologists, by saving time so that they can use their time for more significant work. Generative AI is a special class of AI model, which uses patterns and structures learned from existing data and can create new data. Utilizing ChatGPT in Pathology offers a multitude of benefits, encompassing the summarization of patient records and its promising prospects in Digital Pathology, as well as its valuable contributions to education and research in this field. However, certain roadblocks need to be dealt like integrating ChatGPT with image analysis which will act as a revolution in the field of pathology by increasing diagnostic accuracy and precision. The challenges with the use of ChatGPT encompass biases from its training data, the need for ample input data, potential risks related to bias and transparency, and the potential adverse outcomes arising from inaccurate content generation. Generation of meaningful insights from the textual information which will be efficient in processing different types of image data, such as medical images, and pathology slides. Due consideration should be given to ethical and legal issues including bias.