Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Can ChatGPT effectively generate abstracts in orthopedic surgery? A comparative analysis between human-written and ChatGPT-generated scientific abstracts
0
Zitationen
6
Autoren
2026
Jahr
Abstract
Although ChatGPT, particularly GPT 4.0, can generate abstracts that meet structural requirements and reproduce surface-level elements of academic style, significant limitations remain in content accuracy, originality, and ethical considerations. Key messages What is already known on this topic: With the expanding application of artificial intelligence (AI) techniques, the development of large language models (LLMs) has enabled the generation of natural language with enhanced performance, driven by improved context handling, broader multimodal capabilities, and optimized architectures. However, their specific capacity to generate structurally compliant and ethically acceptable abstracts in the field of orthopedic surgery remains unclear. What this study adds: This study demonstrates that while GPT-4.0 achieves superior adherence to formatting and word counts compared to GPT-3.5, both models frequently generate inaccurate conclusions and exhibit high plagiarism rates, despite being difficult for human reviewers to distinguish from human-written text. How this study might affect research, practice, or policy: Although ChatGPT shows potential as a supportive tool for generating orthopedic research abstracts, our overall findings emphasize that its unregulated or exclusive use introduces significant ethical and practical concerns. To ensure the integrity of academic publishing, it is imperative to establish clear, field-specific guidelines that govern the responsible application of LLMs in scientific writing.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.260 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.116 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.493 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 · 5.438 Zit.