{"title":"Assessing appropriate responses to ACR urologic imaging scenarios using ChatGPT and Bard","authors":"Sishir Doddi , Taryn Hibshman , Oscar Salichs , Kaustav Bera , Charit Tippareddy , Nikhil Ramaiya , Sree Harsha Tirumani","doi":"10.1067/j.cpradiol.2023.10.022","DOIUrl":null,"url":null,"abstract":"<div><p>Artificial intelligence (AI) has recently become a trending tool and topic regarding productivity especially with publicly available free services such as ChatGPT and Bard. In this report, we investigate if two widely available chatbots chatGPT and Bard, are able to show consistent accurate responses for the best imaging modality for urologic clinical situations and if they are in line with American College of Radiology (ACR) Appropriateness Criteria (AC). All clinical scenarios provided by the ACR were inputted into ChatGPT and Bard with result compared to the ACR AC and recorded. Both chatbots had an appropriate imaging modality rate of of 62% and no significant difference in proportion of correct imaging modality was found overall between the two services (p>0.05). The results of our study found that both ChatGPT and Bard are similar in their ability to suggest the most appropriate imaging modality in a variety of urologic scenarios based on ACR AC criteria. Nonetheless, both chatbots lack consistent accuracy and further development is necessary for implementation in clinical settings. For proper use of these AI services in clinical decision making, further developments are needed to improve the workflow of physicians.</p></div>","PeriodicalId":51617,"journal":{"name":"Current Problems in Diagnostic Radiology","volume":"53 2","pages":"Pages 226-229"},"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/S0363018823001755","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}
引用次数: 0
Abstract
Artificial intelligence (AI) has recently become a trending tool and topic regarding productivity especially with publicly available free services such as ChatGPT and Bard. In this report, we investigate if two widely available chatbots chatGPT and Bard, are able to show consistent accurate responses for the best imaging modality for urologic clinical situations and if they are in line with American College of Radiology (ACR) Appropriateness Criteria (AC). All clinical scenarios provided by the ACR were inputted into ChatGPT and Bard with result compared to the ACR AC and recorded. Both chatbots had an appropriate imaging modality rate of of 62% and no significant difference in proportion of correct imaging modality was found overall between the two services (p>0.05). The results of our study found that both ChatGPT and Bard are similar in their ability to suggest the most appropriate imaging modality in a variety of urologic scenarios based on ACR AC criteria. Nonetheless, both chatbots lack consistent accuracy and further development is necessary for implementation in clinical settings. For proper use of these AI services in clinical decision making, further developments are needed to improve the workflow of physicians.
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.