Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Assessing the effectiveness of artificial intelligence (AI) in prioritising CT head interpretation: study protocol for a stepped-wedge cluster randomised trial (ACCEPT-AI)
7
Zitationen
15
Autoren
2024
Jahr
Abstract
The study will be conducted in accordance with the principles of Good Clinical Practice. The protocol was approved by the Research Ethics Committee of East Midlands (Leicester Central), in May 2023 (REC (Research Ethics Committee) 23/EM/0108). Results will be published in peer-reviewed journals and disseminated in scientific findings (ClinicalTrials.gov: NCT06027411) TRIAL REGISTRATION NUMBER: NCT06027411.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.545 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.436 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.935 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 · 5.589 Zit.
Autoren
Institutionen
- King's College London(GB)
- Guy's and St Thomas' NHS Foundation Trust(GB)
- St Thomas' Hospital(GB)
- Northumbria Healthcare NHS Foundation Trust(GB)
- Oxford University Hospitals NHS Trust(GB)
- University of Derby(GB)
- Canterbury Christ Church University(GB)
- Homerton University Hospital NHS Foundation Trust(GB)
- NHS Greater Glasgow and Clyde(GB)
- Queen Elizabeth University Hospital(GB)