Comparative Performance of ChatGPT and Bard in a Text-Based Radiology Knowledge Assessment.

Bard ChatGPT Google artificial intelligence chatbot radiology

Journal

Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes
ISSN: 1488-2361
Titre abrégé: Can Assoc Radiol J
Pays: United States
ID NLM: 8812910

Informations de publication

Date de publication:
14 Aug 2023
Historique:
pubmed: 14 8 2023
medline: 14 8 2023
entrez: 14 8 2023
Statut: aheadofprint

Résumé

Bard by Google, a direct competitor to ChatGPT, was recently released. Understanding the relative performance of these different chatbots can provide important insight into their strengths and weaknesses as well as which roles they are most suited to fill. In this project, we aimed to compare the most recent version of ChatGPT, ChatGPT-4, and Bard by Google, in their ability to accurately respond to radiology board examination practice questions. Text-based questions were collected from the 2017-2021 American College of Radiology's Diagnostic Radiology In-Training (DXIT) examinations. ChatGPT-4 and Bard were queried, and their comparative accuracies, response lengths, and response times were documented. Subspecialty-specific performance was analyzed as well. 318 questions were included in our analysis. ChatGPT answered significantly more accurately than Bard (87.11% vs 70.44%, ChatGPT displayed superior radiology knowledge compared to Bard. While both chatbots display reasonable radiology knowledge, they should be used with conscious knowledge of their limitations and fallibility. Both chatbots provided incorrect or illogical answer explanations and did not always address the educational content of the question.

Identifiants

pubmed: 37578849
doi: 10.1177/08465371231193716
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

8465371231193716

Auteurs

Nikhil S Patil (NS)

Michael G. DeGroote School of Medicine, McMaster University, Hamilton, ON, Canada.

Ryan S Huang (RS)

Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada.

Christian B van der Pol (CB)

Department of Diagnostic Imaging, Hamilton Health Sciences, Juravinski Hospital and Cancer Centre, Hamilton, ON, Canada.

Natasha Larocque (N)

Department of Radiology, McMaster University, Hamilton, ON, Canada.

Classifications MeSH