Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
The application of artificial intelligence in veterinary oncology: a scoping review
2
Zitationen
3
Autoren
2025
Jahr
Abstract
The application of AI in veterinary oncology has produced powerful proof-of-concept models, particularly in diagnostics, with a clear potential to augment clinical practice. However, the path from research to clinical implementation is hindered by fundamental challenges, including the data bottleneck and validation gap. To fulfill its transformative potential, the field must prioritize a shift from isolated studies to collaborative, large-scale research efforts that generate standardized, public datasets and emphasize rigorous external validation. By doing so, the community can ensure the development of generalizable AI models that will truly improve cancer care for veterinary patients.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.402 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.270 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.702 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 · 5.507 Zit.