Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
AI-driven abstract generating: evaluating LLMs with a tailored prompt under the PRISMA-A framework
0
Zitationen
5
Autoren
2025
Jahr
Abstract
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.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.336 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.207 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.607 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.776 Zit.
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)
2018 · 5.476 Zit.