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      Is Open Access

      ChatGPT-4.0 vs. Google: Which Provides More Academic Answers to Patients' Questions on Arthroscopic Meniscus Repair?

      research-article
      1 , 2 , 3 , 4 ,
      ,
      Cureus
      Cureus
      arthroscopy, artificial intelligence, chatgpt, google, meniscus, surgery

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          Abstract

          Purpose

          The purpose of this study was to evaluate the ability of a Chat Generative Pre-trained Transformer (ChatGPT) to provide academic answers to frequently asked questions using a comparison with Google web search FAQs and answers. This study attempted to determine what patients ask on Google and ChatGPT and whether ChatGPT and Google provide factual information for patients about arthroscopic meniscus repair.

          Method

          A cleanly installed Google Chrome browser and ChatGPT were used to ensure no individual cookies, browsing history, other side data, or sponsored sites. The term "arthroscopic meniscus repair" was entered into the Google Chrome browser and ChatGPT. The first 15 frequently asked questions (FAQs), answers, and sources of answers to FAQs were identified from both ChatGPT and Google search engines.

          Results

          Timeline of recovery (20%) and technical details (20%) were the most commonly asked question categories of a total of 30 questions. Technical details and timeline of recovery questions were more commonly asked on ChatGPT compared to Google (technical detail: 33.3% vs. 6.6%, p=0.168; timeline of recovery: 26.6% vs. 13.3%, p=0.651). Answers to questions were more commonly from academic websites in website categories in ChatGPT compared to Google (93.3% vs. 20%, p=0.0001). The most common answers to frequently asked questions were academic (20%) and commercial (20%) in Google.

          Conclusion

          Compared to Google, ChatGPT provided significantly fewer references to commercial content and offered responses that were more aligned with academic sources. ChatGPT may be a valuable adjunct in patient education when used under physician supervision, ensuring information aligns with evidence-based practices.

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          Most cited references28

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          The Measurement of Observer Agreement for Categorical Data

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            The potential for artificial intelligence in healthcare

            The complexity and rise of data in healthcare means that artificial intelligence (AI) will increasingly be applied within the field. Several types of AI are already being employed by payers and providers of care, and life sciences companies. The key categories of applications involve diagnosis and treatment recommendations, patient engagement and adherence, and administrative activities. Although there are many instances in which AI can perform healthcare tasks as well or better than humans, implementation factors will prevent large-scale automation of healthcare professional jobs for a considerable period. Ethical issues in the application of AI to healthcare are also discussed.
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              The rise of artificial intelligence in healthcare applications

              Big data and machine learning are having an impact on most aspects of modern life, from entertainment, commerce, and healthcare. Netflix knows which films and series people prefer to watch, Amazon knows which items people like to buy when and where, and Google knows which symptoms and conditions people are searching for. All this data can be used for very detailed personal profiling, which may be of great value for behavioral understanding and targeting but also has potential for predicting healthcare trends. There is great optimism that the application of artificial intelligence (AI) can provide substantial improvements in all areas of healthcare from diagnostics to treatment. It is generally believed that AI tools will facilitate and enhance human work and not replace the work of physicians and other healthcare staff as such. AI is ready to support healthcare personnel with a variety of tasks from administrative workflow to clinical documentation and patient outreach as well as specialized support such as in image analysis, medical device automation, and patient monitoring. In this chapter, some of the major applications of AI in healthcare will be discussed covering both the applications that are directly associated with healthcare and those in the healthcare value chain such as drug development and ambient assisted living.

                Author and article information

                Journal
                Cureus
                Cureus
                2168-8184
                Cureus
                Cureus (Palo Alto (CA) )
                2168-8184
                25 December 2024
                December 2024
                : 16
                : 12
                : e76380
                Affiliations
                [1 ] Orthopedic Surgery, Haseki Training and Research Hospital, Istanbul, TUR
                [2 ] Orthopedic Surgery, Sisli Memorial Hospital, Istanbul, TUR
                [3 ] Orthopedic Surgery, Cesme Alper Cizgenakat State Hospital, Izmir, TUR
                [4 ] Orthopedics and Rehabilitation, Yale University, New Haven, USA
                Author notes
                Article
                10.7759/cureus.76380
                11760333
                39867098
                0930a2d1-85c4-4114-af2d-7f8655876b8c
                Copyright © 2024, Eryilmaz et al.

                This is an open access article distributed under the terms of the Creative Commons Attribution License CC-BY 4.0., which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 25 December 2024
                Categories
                Orthopedics
                Sports Medicine

                arthroscopy,artificial intelligence,chatgpt,google,meniscus,surgery

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