Samuel Ji Quan Koh, Khung Keong Yeo, Jonathan Jiunn-Liang Yap
{"title":"Leveraging ChatGPT to aid patient education on coronary angiogram.","authors":"Samuel Ji Quan Koh, Khung Keong Yeo, Jonathan Jiunn-Liang Yap","doi":"10.47102/annals-acadmedsg.2023138","DOIUrl":null,"url":null,"abstract":"<p><p>Natural-language artificial intelligence (AI) is a promising technological advancement poised to revolutionise the delivery of healthcare. We aim to explore the quality of ChatGPT in providing medical information regarding a common cardiology procedure-the coronary angiogram-and evaluating the potential opportunities and challenges of patient education through this natural-language AI model in the broader context. In a conversational manner, we asked ChatGPT common questions about undergoing a coronary angiogram according to the areas of: description of procedure, indications, contraindications, complications, alternatives, and follow-up. The strengths of the answers given by ChatGPT were that they were generally presented in a comprehensive and systematic fashion, covering most of the major information fields that are required. However, there were certain deficiencies in its responses. These include occasional factual inaccuracies, significant omissions, inaccurate assumptions, and lack of flexibility in recommendations beyond the line of questioning, resulting in the answers being focused solely on the topic. We would expect an increasing number of patients who may choose to seek information about their health through these platforms given their accessibility and perceived reliability. Consequently, it is prudent for healthcare professionals to be cognisant of both the strengths and deficiencies of such models. While these models appear to be good adjuncts for patients to obtain information, they cannot replace the role of a healthcare provider in delivering personalised health advice and management.</p>","PeriodicalId":5,"journal":{"name":"ACS Applied Materials & Interfaces","volume":" ","pages":"374-377"},"PeriodicalIF":8.2000,"publicationDate":"2023-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Materials & Interfaces","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.47102/annals-acadmedsg.2023138","RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATERIALS SCIENCE, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
Natural-language artificial intelligence (AI) is a promising technological advancement poised to revolutionise the delivery of healthcare. We aim to explore the quality of ChatGPT in providing medical information regarding a common cardiology procedure-the coronary angiogram-and evaluating the potential opportunities and challenges of patient education through this natural-language AI model in the broader context. In a conversational manner, we asked ChatGPT common questions about undergoing a coronary angiogram according to the areas of: description of procedure, indications, contraindications, complications, alternatives, and follow-up. The strengths of the answers given by ChatGPT were that they were generally presented in a comprehensive and systematic fashion, covering most of the major information fields that are required. However, there were certain deficiencies in its responses. These include occasional factual inaccuracies, significant omissions, inaccurate assumptions, and lack of flexibility in recommendations beyond the line of questioning, resulting in the answers being focused solely on the topic. We would expect an increasing number of patients who may choose to seek information about their health through these platforms given their accessibility and perceived reliability. Consequently, it is prudent for healthcare professionals to be cognisant of both the strengths and deficiencies of such models. While these models appear to be good adjuncts for patients to obtain information, they cannot replace the role of a healthcare provider in delivering personalised health advice and management.
期刊介绍:
ACS Applied Materials & Interfaces is a leading interdisciplinary journal that brings together chemists, engineers, physicists, and biologists to explore the development and utilization of newly-discovered materials and interfacial processes for specific applications. Our journal has experienced remarkable growth since its establishment in 2009, both in terms of the number of articles published and the impact of the research showcased. We are proud to foster a truly global community, with the majority of published articles originating from outside the United States, reflecting the rapid growth of applied research worldwide.