Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Development of an AI model for pneumothorax imaging: Dataset and model optimization strategies for real-world deployment
0
Zitationen
4
Autoren
2025
Jahr
Abstract
The AI model shows potential in pneumothorax detection, but performance is influenced by data diversity, image quality, and clinical complexity. The model struggles to identify key areas in complex cases, indicating a need for attention mechanisms or region proposal networks (RPN). Expanding the dataset, optimizing preprocessing, and training separate models for different image locations could enhance performance further.
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.