Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Artificial intelligence and the NHS: a qualitative exploration of the factors influencing adoption
42
Zitationen
1
Autoren
2021
Jahr
Abstract
BACKGROUND: AI has the potential to improve healthcare. However, there is limited research investigating the factors which influence the adoption of AI within a healthcare system. RESEARCH AIMS: I aimed to use innovation theory to understand the barriers and facilitators that influence AI adoption in the NHS; and to explore solutions to overcome these barriers, and examine these factors, particularly within radiology, pathology and general practice. METHODOLOGY: Twelve semi-structured, one-to-one interviews were conducted with key informants. Interview data were analysed using thematic analysis. FINDINGS: A range of barriers and facilitators to the adoption of AI within the NHS were identified, including IT infrastructure and language clarity. Several solutions to overcome the barriers were proposed by participants, including education strategies and innovation champions. CONCLUSION: Future research should explore the importance of IT infrastructure in supporting AI adoption, examine the terminology around AI and explore specialty-specific barriers to AI adoption in greater depth.
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.