{"title":"Evaluation and Comparison of the Knowledge Levels of Current Artificial Intelligence Programs on Retinal/Vitreous Diseases and Treatment Methods.","authors":"Eyupcan Sensoy, Mehmet Citirik","doi":"10.4103/joco.joco_192_23","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose: </strong>To evaluate the answers to multiple-choice questions about retina and vitreous diseases and treatment modalities of Chat Generative Pre-Trained Transformer (ChatGPT), Bard, and Bing artificial intelligence chatbots, examining the level of knowledge about these subjects, and investigating the existence of their superiority over each other.</p><p><strong>Methods: </strong>Forty-six questions related to retinal and vitreous diseases and treatment modalities were asked to ChatGPT, Bing, and Bard chatbots.</p><p><strong>Results: </strong>The Bing artificial intelligence chatbot correctly answered 76.1% of the questions. ChatGPT and Bard artificial intelligence chatbots correctly answered 60.9% of the questions. No statistically significant difference was observed between the rates of correct and incorrect answers to the questions on the three artificial intelligence chatbots (<i>P</i> = 0.206).</p><p><strong>Conclusions: </strong>Artificial intelligence chatbots can be used to access accurate information about retinal and vitreous diseases and treatment modalities. However, the information obtained may not always be correct, and care should be taken about its use and results.</p>","PeriodicalId":15423,"journal":{"name":"Journal of Current Ophthalmology","volume":"36 1","pages":"78-81"},"PeriodicalIF":1.2000,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11567598/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Current Ophthalmology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4103/joco.joco_192_23","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q3","JCRName":"OPHTHALMOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Purpose: To evaluate the answers to multiple-choice questions about retina and vitreous diseases and treatment modalities of Chat Generative Pre-Trained Transformer (ChatGPT), Bard, and Bing artificial intelligence chatbots, examining the level of knowledge about these subjects, and investigating the existence of their superiority over each other.
Methods: Forty-six questions related to retinal and vitreous diseases and treatment modalities were asked to ChatGPT, Bing, and Bard chatbots.
Results: The Bing artificial intelligence chatbot correctly answered 76.1% of the questions. ChatGPT and Bard artificial intelligence chatbots correctly answered 60.9% of the questions. No statistically significant difference was observed between the rates of correct and incorrect answers to the questions on the three artificial intelligence chatbots (P = 0.206).
Conclusions: Artificial intelligence chatbots can be used to access accurate information about retinal and vitreous diseases and treatment modalities. However, the information obtained may not always be correct, and care should be taken about its use and results.
期刊介绍:
Peer Review under the responsibility of Iranian Society of Ophthalmology Journal of Current Ophthalmology, the official publication of the Iranian Society of Ophthalmology, is a peer-reviewed, open-access, scientific journal that welcomes high quality original articles related to vision science and all fields of ophthalmology. Journal of Current Ophthalmology is the continuum of Iranian Journal of Ophthalmology published since 1969.