Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Performance of adult-trained artificial intelligence models in paediatric imaging—a scoping review
0
Zitationen
5
Autoren
2026
Jahr
Abstract
Question How do artificial intelligence-based radiology tools designed for adults perform when applied to paediatric imaging without additional adaptation? Findings Adult-trained AI models consistently demonstrated reduced performance in children, particularly in those under 2 years, with detection tasks showing the most severe deterioration. Clinical relevance Healthcare professionals should not assume that adult-trained radiology AI tools intended for adult use can be directly applied to the paediatric population without validation, additional training or fine-tuning, particularly for the youngest age groups.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.231 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.084 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.444 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 · 5.423 Zit.