Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Five essential features for adoption of clinical risk prediction tools: Insights from the VOCAL-Penn score
0
Zitationen
3
Autoren
2025
Jahr
Abstract
Using the VPS as a grounding example, our findings identify 5 domains-efficiency, accessibility, transparency, accuracy, and generalizability-that inform the development and dissemination of future tools. By aligning tool design with real-world clinical needs, this framework may support broader adoption and more equitable implementation of medical risk prediction tools.
Ähnliche Arbeiten
"Why Should I Trust You?"
2016 · 14.210 Zit.
A Comprehensive Survey on Graph Neural Networks
2020 · 8.586 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.100 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.466 Zit.
Artificial intelligence in healthcare: past, present and future
2017 · 4.382 Zit.