• Türkçe
    • English
  • English 
    • Türkçe
    • English
  • Login
View Item 
  •   RTEÜ
  • Araştırma Çıktıları | TR-Dizin | WoS | Scopus | PubMed
  • Scopus İndeksli Yayınlar Koleksiyonu
  • View Item
  •   RTEÜ
  • Araştırma Çıktıları | TR-Dizin | WoS | Scopus | PubMed
  • Scopus İndeksli Yayınlar Koleksiyonu
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

Accuracy and readability of ChatGPT on potential complications of interventional radiology procedures: AI-powered patient interviewing

Access

info:eu-repo/semantics/closedAccess

Date

2024

Author

Kaba, Esat
Beyazal, Mehmet
Çeliker, Fatma Beyazal
Yel, İbrahim
Vogl, Thomas J

Metadata

Show full item record

Citation

Kaba, E., Beyazal, M., Çeliker, F. B., Yel, İ., & Vogl, T. J. (2024). Accuracy and Readability of ChatGPT on Potential Complications of Interventional Radiology Procedures: AI-Powered Patient Interviewing. Academic radiology, S1076-6332(24)00791-8. Advance online publication. https://doi.org/10.1016/j.acra.2024.10.028

Abstract

Rationale and Objectives: It is crucial to inform the patient about potential complications and obtain consent before interventional radiology procedures. In this study, we investigated the accuracy, reliability, and readability of the information provided by ChatGPT-4 about potential complications of interventional radiology procedures. Materials and Methods: Potential major and minor complications of 25 different interventional radiology procedures (8 non-vascular, 17 vascular) were asked to ChatGPT-4 chatbot. The responses were evaluated by two experienced interventional radiologists (>25 years and 10 years of experience) using a 5-point Likert scale according to Cardiovascular and Interventional Radiological Society of Europe guidelines. The correlation between the two interventional radiologists' scoring was evaluated by the Wilcoxon signed-rank test, Intraclass Correlation Coefficient (ICC), and Pearson correlation coefficient (PCC). In addition, readability and complexity were quantitatively assessed using the Flesch-Kincaid Grade Level, Flesch Reading Ease scores, and Simple Measure of Gobbledygook (SMOG) index. Results: Interventional radiologist 1 (IR1) and interventional radiologist 2 (IR2) gave 104 and 109 points, respectively, out of a potential 125 points for the total of all procedures. There was no statistically significant difference between the total scores of the two IRs (p = 0.244). The IRs demonstrated high agreement across all procedure ratings (ICC = 0.928). Both IRs scored 34 out of 40 points for the eight non-vascular procedures. 17 vascular procedures received 70 points out of 85 from IR1 and 75 from IR2. The agreement between the two observers' assessments was good, with PCC values of 0.908 and 0.896 for non-vascular and vascular procedures, respectively. Readability levels were overall low. The mean Flesch-Kincaid Grade Level, Flesch Reading Ease scores, and SMOG index were 12.51 ± 1.14 (college level) 30.27 ± 8.38 (college level), and 14.46 ± 0.76 (college level), respectively. There was no statistically significant difference in readability between non-vascular and vascular procedures (p = 0.16). Conclusion: ChatGPT-4 demonstrated remarkable performance, highlighting its potential to enhance accessibility to information about interventional radiology procedures and support the creation of educational materials for patients. Based on the findings of our study, while ChatGPT provides accurate information and shows no evidence of hallucinations, it is important to emphasize that a high level of education and health literacy are required to fully comprehend its responses.

Source

Academic Radiology

URI

https://doi.org/10.1016/j.acra.2024.10.028
https://hdl.handle.net/11436/9805

Collections

  • PubMed İndeksli Yayınlar Koleksiyonu [2443]
  • Scopus İndeksli Yayınlar Koleksiyonu [5931]
  • TF, Dahili Tıp Bilimleri Bölümü Koleksiyonu [1559]



DSpace software copyright © 2002-2015  DuraSpace
Contact Us | Send Feedback
Theme by 
@mire NV
 

 




| Instruction | Guide | Contact |

DSpace@RTEÜ

by OpenAIRE
Advanced Search

sherpa/romeo

Browse

All of DSpaceCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsTypeLanguageDepartmentCategoryPublisherAccess TypeInstitution AuthorThis CollectionBy Issue DateAuthorsTitlesSubjectsTypeLanguageDepartmentCategoryPublisherAccess TypeInstitution Author

My Account

LoginRegister

Statistics

View Google Analytics Statistics

DSpace software copyright © 2002-2015  DuraSpace
Contact Us | Send Feedback
Theme by 
@mire NV
 

 


|| Guide|| Instruction || Library || Recep Tayyip Erdoğan University || OAI-PMH ||

Recep Tayyip Erdoğan University, Rize, Turkey
If you find any errors in content, please contact:

Creative Commons License
Recep Tayyip Erdoğan University Institutional Repository is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 4.0 Unported License..

DSpace@RTEÜ:


DSpace 6.2

tarafından İdeal DSpace hizmetleri çerçevesinde özelleştirilerek kurulmuştur.