Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Assessing Interrater Reliability of ChatGPT-4 and Orthopaedic Clinicians in Radiographic Fracture Classification
0
Zitationen
13
Autoren
2025
Jahr
Abstract
Although ChatcGPT-4 showed promise in classifying basic fracture features, it was not yet at a level comparable to experts, especially with more nuanced interpretations. These findings suggest that the use of AI is more effective as an adjunct to the judgment of trained clinicians rather than a replacement for it.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.316 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.177 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.575 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 · 5.468 Zit.