Cargando…
Human–machine teaming is key to AI adoption: clinicians’ experiences with a deployed machine learning system
While a growing number of machine learning (ML) systems have been deployed in clinical settings with the promise of improving patient care, many have struggled to gain adoption and realize this promise. Based on a qualitative analysis of coded interviews with clinicians who use an ML-based system fo...
Autores principales: | Henry, Katharine E., Kornfield, Rachel, Sridharan, Anirudh, Linton, Robert C., Groh, Catherine, Wang, Tony, Wu, Albert, Mutlu, Bilge, Saria, Suchi |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9304371/ https://www.ncbi.nlm.nih.gov/pubmed/35864312 http://dx.doi.org/10.1038/s41746-022-00597-7 |
Ejemplares similares
-
Designing AI Systems With Human-Machine Teams
por: Saenz, Maria
Publicado: (2020) -
Better medicine through machine learning: What’s real, and what’s artificial?
por: Saria, Suchi, et al.
Publicado: (2018) -
AI-deploying organizations are key to addressing ‘perfect storm’ of AI risks
por: Curtis, Caitlin, et al.
Publicado: (2022) -
Artificial Intelligence (AI) to the Rescue: Deploying Machine Learning to Bridge the Biorelevance Gap in Antioxidant Assays
por: Idowu, Sunday Olakunle, et al.
Publicado: (2020) -
AI and machine learning
por: Rahman, Was
Publicado: (2020)