Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
The ethics of simplification: balancing patient autonomy, comprehension, and accuracy in AI-generated radiology reports
4
Zitationen
9
Autoren
2025
Jahr
Abstract
Our findings highlight an ethical tension between improving readability and maintaining clinical accuracy. While 7th-grade readability remains an ethical ideal, current AI tools cannot reliably produce accurate reports below the 11th-grade level. Ethical implementation of AI-generated reporting should include layered communication strategies and model transparency to safeguard patient autonomy and comprehension.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.400 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.261 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.695 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.781 Zit.
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)
2018 · 5.506 Zit.