Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
A bibliometric analysis of the 50 most cited articles about artificial intelligence in electrocardiogram
0
Zitationen
5
Autoren
2025
Jahr
Abstract
This bibliometric analysis provides clinicians and researchers with an overview of evolution and progression of AI in the domain of ECG. Improved collaborations among different countries and institutions are essential for achieving advancements in the utilization of AI in ECG.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.436 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.311 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.753 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 · 5.523 Zit.