Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Investigating Data Diversity and Model Robustness of AI Applications in Palliative Care and Hospice: Protocol for Scoping Review
2024·2 Zitationen·JMIR Research ProtocolsOpen Access
Volltext beim Verlag öffnen2
Zitationen
12
Autoren
2024
Jahr
Abstract
DERR1-10.2196/56353.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.549 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.443 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.941 Zit.
BioBERT: a pre-trained biomedical language representation model for biomedical text mining
2019 · 6.792 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.781 Zit.
Autoren
Institutionen
- Emory University(US)
- Yale University(US)
- Ankara University(TR)
- Woodruff Health Sciences Center(US)
- University of California, Los Angeles(US)
- VA Greater Los Angeles Healthcare System(US)
- Brigham and Women's Hospital(US)
- Harvard University(US)
- Dana-Farber Cancer Institute(US)
- VA Palo Alto Health Care System(US)
- Stanford University(US)
Themen
Artificial Intelligence in Healthcare and EducationMachine Learning in HealthcareExplainable Artificial Intelligence (XAI)