Comparative analysis of ChatGPT and Gemini (Bard) in medical inquiry: a scoping review
Open accessAbstract
Introduction: Artificial intelligence and machine learning are popular interconnected technologies. AI chatbots like ChatGPT and Gemini show considerable promise in medical inquiries. This scoping review aims to assess the accuracy and response length (in characters) of ChatGPT and Gemini in medical applications. Methods: The eligible databases were searched to find studies published in English from January 1 to October 20, 2023. The inclusion criteria consisted of studies that focused on using AI in medicine and assessed outcomes based on the accuracy and character count (length) of ChatGPT and Gemini. Data collected from the studies included the first author's name, the country where the study was conducted, the type of study design, publication year, sample size, medical speciality, and the accuracy and response length. Results: The initial search identified 64 papers, with 11 meeting the inclusion criteria, involving 1,177 samples. ChatGPT showed higher accuracy in radiology (87.43% vs. Gemini's 71%) and shorter responses (907 vs. 1,428 characters). Similar trends were noted in other specialties. However, Gemini outperformed ChatGPT in emergency scenarios (87% vs. 77%) and in renal diets with low potassium and high phosphorus (79% vs. 60% and 100% vs. 77%). Statistical analysis confirms that ChatGPT has greater accuracy and shorter responses than Gemini in medical studies, with a p-value of <.001 for both metrics. Conclusion: This Scoping review suggests that ChatGPT may demonstrate higher accuracy and provide shorter responses than Gemini in medical studies.
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Current research on AI in nursing education is divided and heterogeneous in design, setting, AI tools evaluated, and outcomes.
“Although the number of works that investigate the topic of AI in education is constantly increasing, the current research is still divided, and the studies are diverse in terms of design, setting, AI tools evaluated, and their outcomes [9].”
From HOW AI TOOLS (LIKE CHATGPT/GEMINI) AFFECT CRITICAL THINKING IN NURSING STUDENTS. A SYSTEMATIC REVIEW (2026) · cites this paper as [9]
The Results (Characteristics of the included studies; page not specified) show studies across countries and medical specialties, with differing accuracy outcomes. The Discussion also notes variability across specialties. But this review compares ChatGPT and Gemini in medical inquiries; it does not establish that research on AI in nursing education is divided or diverse in study design and AI tools evaluated. (LLM, conf=0.82)
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- Authors
- Fattah, F. H., Salih, A. M., Salih, A. M., Asaad, S. K., Ghafour, A. K., Bapir, R., Abdalla, B. A., Othman, S., Ahmed, S. M., Hasan, S. J., Mahmood, Y. M., & Kakamad, F. H.
- Affiliations
- University of Sulaimani (IQ)
- Corresponding author
- Kakamad, Fahmi H.
- Venue
- Frontiers in Digital Health
- Publisher
- Frontiers Media SA
- Published
- 2025-02-03
- Volume
- 7
- Pages
- 1482712-1482712
- ISSN
- 2673-253X (ISSN-L)
- PMC
- PMC11830737
- OpenAlex
- W4407111166
- Cited by
- 50
- References
- 26
- Citations by year
- 2026: 32 · 2025: 18
- FWCI
- 12.04
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Frontiers in Digital Health (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Health Sciences › Health Professions › Health Information Management › Artificial Intelligence in Healthcare
- Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
- Keywords
- ChatGPT, large language models, AI chatbots, medical question answering, diagnostic accuracy, response length, radiology, emergency medicine, renal diet, artificial intelligence in healthcare
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