Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Development of a Determinant Framework to Guide the Translation of AI Systems in Clinical Care
0
Zitationen
1
Autoren
2023
Jahr
Abstract
Artificial Intelligence (AI) tools are increasingly being implemented in clinical settings, but there are inadequate studies evaluating the human, social, and organizational aspects of their integration, performance, and usage. Additionally, there is a lack of holistic frameworks for the implementation of AI systems in clinical spaces. This study aims to assess the socio-technical and systems factors that influence the implementation of AI tools in clinical settings and adapt it to create a predictive evaluation framework. Surveys and in-depth interviews will be conducted with staff at the University of Illinois Health center who interact with the Epic Sepsis tool. The data will be analyzed using Dedoose software. Based on the results, a framework and checklist will be developed to guide the predictive evaluation of AI tools in clinical settings. The checklist will be evaluated during the development of the DPI-diabetes AI tool for completeness and usefulness. This study will help in developing a new determinant framework.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.260 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.116 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.493 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.776 Zit.
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)
2018 · 5.438 Zit.