Cargando…
Evaluation framework to guide implementation of AI systems into healthcare settings
OBJECTIVES: To date, many artificial intelligence (AI) systems have been developed in healthcare, but adoption has been limited. This may be due to inappropriate or incomplete evaluation and a lack of internationally recognised AI standards on evaluation. To have confidence in the generalisability o...
Autores principales: | Reddy, Sandeep, Rogers, Wendy, Makinen, Ville-Petteri, Coiera, Enrico, Brown, Pieta, Wenzel, Markus, Weicken, Eva, Ansari, Saba, Mathur, Piyush, Casey, Aaron, Kelly, Blair |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8513218/ https://www.ncbi.nlm.nih.gov/pubmed/34642177 http://dx.doi.org/10.1136/bmjhci-2021-100444 |
Ejemplares similares
-
Application of a Comprehensive Evaluation Framework to COVID-19 Studies: Systematic Review of Translational Aspects of Artificial Intelligence in Health Care
por: Casey, Aaron Edward, et al.
Publicado: (2023) -
Multivariable Analysis of Nutritional and Socio-Economic Profiles Shows Differences in Incident Anemia for Northern and Southern Jiangsu in China
por: Mutter, Stefan, et al.
Publicado: (2017) -
Moving beyond algorithmic accuracy to improving user interaction with clinical AI
por: Berkovsky, Shlomo, et al.
Publicado: (2023) -
Exploring stakeholder attitudes towards AI in clinical practice
por: Scott, Ian A, et al.
Publicado: (2021) -
Implementation frameworks for end-to-end clinical AI: derivation of the SALIENT framework
por: van der Vegt, Anton H, et al.
Publicado: (2023)