Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
The Significance of AI in Evidence-based Practice in Healthcare
0
Zitationen
2
Autoren
2025
Jahr
Abstract
This paper examines the transformative potential of Artificial Intelligence (AI) in enhancing evidence-based practice (EBP) within healthcare. By leveraging AI-driven clinical decision support systems, natural language processing, and advanced diagnostic tools, the study explores how these technologies can streamline the synthesis and application of medical evidence to improve clinical decision-making and patient outcomes. Through a comprehensive literature review and analysis of case studies, we highlight the significant impact of AI on reducing administrative burdens, minimizing diagnostic errors, and enabling personalized care. In addition to these benefits, the paper also addresses key challenges such as ethical concerns, technical limitations, and potential biases. The findings underscore the need for continued interdisciplinary collaboration and the development of transparent and adaptive AI systems to ensure that these innovations effectively complement and enhance clinical workflows.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.391 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.257 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.685 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 · 5.501 Zit.