{"title":"ChatGPT放射学出版物分析：迄今为止的文献。","authors":"Kaustav Bera MD, Gregory O’Connor MD, Sirui Jiang MD, Sree Harsha Tirumani MD, Nikhil Ramaiya MD","doi":"10.1067/j.cpradiol.2023.10.013","DOIUrl":null,"url":null,"abstract":"<div><h3>Objective</h3><p>To perform a detailed qualitative and quantitative analysis of the published literature on ChatGPT and radiology in the nine months since its public release, detailing the scope of the work in the short timeframe.</p></div><div><h3>Methods</h3><p>A systematic literature search was carried out of the MEDLINE, EMBASE databases through August 15, 2023 for articles that were focused on ChatGPT and imaging/radiology. Articles were classified into original research and reviews/perspectives. Quantitative analysis was carried out by two experienced radiologists using objective scoring systems for evaluating original and non-original research.</p></div><div><h3>Results</h3><p>51 articles were published involving ChatGPT and radiology/imaging dating from 26 Jan 2023 to the last article published on 14 Aug 2023. 23 articles were original research while the rest included reviews/perspectives or brief communications. For quantitative analysis scored by two readers, we included 23 original research and 17 non-original research articles (after excluding 11 letters as responses to previous articles). Mean score for original research was 3.20 out of 5 (across five questions), while mean score for non-original research was 1.17 out of 2 (across six questions). Mean score grading performance of ChatGPT in original research was 3.20 out of five (across two questions).</p></div><div><h3>Discussion</h3><p>While it is early days for ChatGPT and its impact in radiology, there has already been a plethora of articles talking about the multifaceted nature of the tool and how it can impact every aspect of radiology from patient education, pre-authorization, protocol selection, generating differentials, to structuring radiology reports. Most articles show impressive performance of ChatGPT which can only improve with more research and improvements in the tool itself. There have also been several articles which have highlighted the limitations of ChatGPT in its current iteration, which will allow radiologists and researchers to improve these areas.</p></div>","PeriodicalId":51617,"journal":{"name":"Current Problems in Diagnostic Radiology","volume":"53 2","pages":"Pages 215-225"},"PeriodicalIF":1.5000,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Analysis of ChatGPT publications in radiology: Literature so far\",\"authors\":\"Kaustav Bera MD, Gregory O’Connor MD, Sirui Jiang MD, Sree Harsha Tirumani MD, Nikhil Ramaiya MD\",\"doi\":\"10.1067/j.cpradiol.2023.10.013\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Objective</h3><p>To perform a detailed qualitative and quantitative analysis of the published literature on ChatGPT and radiology in the nine months since its public release, detailing the scope of the work in the short timeframe.</p></div><div><h3>Methods</h3><p>A systematic literature search was carried out of the MEDLINE, EMBASE databases through August 15, 2023 for articles that were focused on ChatGPT and imaging/radiology. Articles were classified into original research and reviews/perspectives. Quantitative analysis was carried out by two experienced radiologists using objective scoring systems for evaluating original and non-original research.</p></div><div><h3>Results</h3><p>51 articles were published involving ChatGPT and radiology/imaging dating from 26 Jan 2023 to the last article published on 14 Aug 2023. 23 articles were original research while the rest included reviews/perspectives or brief communications. For quantitative analysis scored by two readers, we included 23 original research and 17 non-original research articles (after excluding 11 letters as responses to previous articles). Mean score for original research was 3.20 out of 5 (across five questions), while mean score for non-original research was 1.17 out of 2 (across six questions). Mean score grading performance of ChatGPT in original research was 3.20 out of five (across two questions).</p></div><div><h3>Discussion</h3><p>While it is early days for ChatGPT and its impact in radiology, there has already been a plethora of articles talking about the multifaceted nature of the tool and how it can impact every aspect of radiology from patient education, pre-authorization, protocol selection, generating differentials, to structuring radiology reports. Most articles show impressive performance of ChatGPT which can only improve with more research and improvements in the tool itself. There have also been several articles which have highlighted the limitations of ChatGPT in its current iteration, which will allow radiologists and researchers to improve these areas.</p></div>\",\"PeriodicalId\":51617,\"journal\":{\"name\":\"Current Problems in Diagnostic Radiology\",\"volume\":\"53 2\",\"pages\":\"Pages 215-225\"},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2024-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Current Problems in Diagnostic Radiology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0363018823001664\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current Problems in Diagnostic Radiology","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0363018823001664","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
Analysis of ChatGPT publications in radiology: Literature so far
Objective
To perform a detailed qualitative and quantitative analysis of the published literature on ChatGPT and radiology in the nine months since its public release, detailing the scope of the work in the short timeframe.
Methods
A systematic literature search was carried out of the MEDLINE, EMBASE databases through August 15, 2023 for articles that were focused on ChatGPT and imaging/radiology. Articles were classified into original research and reviews/perspectives. Quantitative analysis was carried out by two experienced radiologists using objective scoring systems for evaluating original and non-original research.
Results
51 articles were published involving ChatGPT and radiology/imaging dating from 26 Jan 2023 to the last article published on 14 Aug 2023. 23 articles were original research while the rest included reviews/perspectives or brief communications. For quantitative analysis scored by two readers, we included 23 original research and 17 non-original research articles (after excluding 11 letters as responses to previous articles). Mean score for original research was 3.20 out of 5 (across five questions), while mean score for non-original research was 1.17 out of 2 (across six questions). Mean score grading performance of ChatGPT in original research was 3.20 out of five (across two questions).
Discussion
While it is early days for ChatGPT and its impact in radiology, there has already been a plethora of articles talking about the multifaceted nature of the tool and how it can impact every aspect of radiology from patient education, pre-authorization, protocol selection, generating differentials, to structuring radiology reports. Most articles show impressive performance of ChatGPT which can only improve with more research and improvements in the tool itself. There have also been several articles which have highlighted the limitations of ChatGPT in its current iteration, which will allow radiologists and researchers to improve these areas.
期刊介绍：
Current Problems in Diagnostic Radiology covers important and controversial topics in radiology. Each issue presents important viewpoints from leading radiologists. High-quality reproductions of radiographs, CT scans, MR images, and sonograms clearly depict what is being described in each article. Also included are valuable updates relevant to other areas of practice, such as medical-legal issues or archiving systems. With new multi-topic format and image-intensive style, Current Problems in Diagnostic Radiology offers an outstanding, time-saving investigation into current topics most relevant to radiologists.
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