Leveraging artificial intelligence chatbots for anemia prevention: A comparative study of ChatGPT-3.5, copilot, and Gemini outputs against Google Search results
AI-generated texts on anemia were found to be more readable and easier to understand than traditional web-based texts, with Gemini demonstrating the highest level of understandability. Moving forward, improvements in prompts will be necessary to enhance the integration of visual elements that encourage actionable responses in AI chatbots.
Authors
- Emi Furukawa (ORCID: https://orcid.org/0000-0002-1431-4786)
- Hiroko Okada (ORCID: https://orcid.org/0000-0001-7877-9753)
- Tsuyoshi Okuhara (ORCID: https://orcid.org/0000-0002-6251-3587)
- Takahiro Kiuchi (ORCID: https://orcid.org/0000-0001-5934-0681)
- Shinya Ito (ORCID: https://orcid.org/0000-0001-8544-4871)
Institutions
- University of Tokyo Hospital (JP)
- Department of Health (IE)
- University hospital Medical Information Network (JP)
- Kitasato University (JP)
- The University of Tokyo (JP)
Publication Details
- Journal
- PEC Innovation
- Published
- 2025-04-05
- DOI
- https://doi.org/10.1016/j.pecinn.2025.100390
- Citations
- 5
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 3.27
Funders
- Japan Society for the Promotion of Science