Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Insufficient reporting quality in large language model studies in the field of radiology
0
Zitationen
8
Autoren
2026
Jahr
Abstract
Numerous studies on large language models (LLMs) in radiology lack standardized methodologies, leading to high variability and inconsistent reporting. Our review demonstrated insufficiency in key elements for LLM research, particularly in model details and output probability. Better reporting and adherence to key elements are essential for enhancing transparency and reproducibility in future LLM research.
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.