AI-driven abstract generating: evaluating LLMs with a tailored prompt under the PRISMA-A framework
Both LLMs demonstrated the ability to generate PRISMA-A-compliant abstracts from systematic reviews, with ChatGPT-4o consistently achieving higher quality scores than Gemini Pro. While tested in orthodontics, the approach holds potential for broader applications across evidence-based dental and medical research. Systematic reviews and meta-analyses are essential to evidence-based dentistry but can be challenging and time-consuming to report in accordance with established standards. The structured prompt developed in this study may assist researchers in generating PRISMA-A-compliant outputs more efficiently, helping to accelerate the completion and standardisation of high-level clinical evidence reporting.
Authors
- Kübra Gülnur Topsakal (ORCID: https://orcid.org/0000-0002-2717-3492)
- Şule Gökmen (ORCID: https://orcid.org/0000-0002-0677-3472)
- Gizem Boztaş Demi̇r (ORCID: https://orcid.org/0000-0002-9871-8226)
- Serkan Görgülü (ORCID: https://orcid.org/0000-0003-1617-573X)
- Yağızalp Sükut
Institutions
- Gülhane Askerî Tıp Akademisi (TR)
- Sağlık Bilimleri Üniversitesi (TR)
Publication Details
- Journal
- BMC Oral Health
- Published
- 2025-10-10
- DOI
- https://doi.org/10.1186/s12903-025-06982-4
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00