Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Human-AI Collaboration in Healthcare: A Review and Research Agenda
60
Zitationen
3
Autoren
2021
Jahr
Abstract
Advances in Artificial Intelligence (AI) have led to the rise of human-AI collaboration. In healthcare, such collaboration could mitigate the shortage of qualified healthcare workers, assist overworked medical professionals, and improve the quality of healthcare. However, many challenges remain, such as investigating biases in clinical decision-making, the lack of trust in AI and adoption issues. While there is a growing number of studies on the topic, they are in disparate fields, and we lack a summary understanding of this research. To address this issue, this study conducts a literature review to examine prior research, identify gaps, and propose future research directions. Our findings indicate that there are limited studies about the evolving and interactive collaboration process in healthcare, the complementarity of humans and AI, the adoption and perception of AI, and the long-term impact on individuals and healthcare organizations. Additionally, more theory-driven research is needed to inform the design, implementation, and use of collaborative AI for healthcare and to realize its benefits.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.339 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.211 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.614 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 · 5.478 Zit.