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Adopting Artificial Intelligence in Public Healthcare: The Effect of Social Power and Learning Algorithms

Although the use of artificial intelligence (AI) in healthcare is still in its early stages, it is important to understand the factors influencing its adoption. Using a qualitative multi-case study of three hospitals in China, we explored the research of factors affecting AI adoption from a social p...

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Detalles Bibliográficos
Autor principal: Sun, Tara Qian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8656642/
https://www.ncbi.nlm.nih.gov/pubmed/34886404
http://dx.doi.org/10.3390/ijerph182312682
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author Sun, Tara Qian
author_facet Sun, Tara Qian
author_sort Sun, Tara Qian
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description Although the use of artificial intelligence (AI) in healthcare is still in its early stages, it is important to understand the factors influencing its adoption. Using a qualitative multi-case study of three hospitals in China, we explored the research of factors affecting AI adoption from a social power perspective with consideration of the learning algorithm abilities of AI systems. Data were collected through semi-structured interviews, participative observations, and document analysis, and analyzed using NVivo 11. We classified six social powers into knowledge-based and non-knowledge-based power structures, revealing a social power pattern related to the learning algorithm ability of AI.
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spelling pubmed-86566422021-12-10 Adopting Artificial Intelligence in Public Healthcare: The Effect of Social Power and Learning Algorithms Sun, Tara Qian Int J Environ Res Public Health Article Although the use of artificial intelligence (AI) in healthcare is still in its early stages, it is important to understand the factors influencing its adoption. Using a qualitative multi-case study of three hospitals in China, we explored the research of factors affecting AI adoption from a social power perspective with consideration of the learning algorithm abilities of AI systems. Data were collected through semi-structured interviews, participative observations, and document analysis, and analyzed using NVivo 11. We classified six social powers into knowledge-based and non-knowledge-based power structures, revealing a social power pattern related to the learning algorithm ability of AI. MDPI 2021-12-01 /pmc/articles/PMC8656642/ /pubmed/34886404 http://dx.doi.org/10.3390/ijerph182312682 Text en © 2021 by the author. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Sun, Tara Qian
Adopting Artificial Intelligence in Public Healthcare: The Effect of Social Power and Learning Algorithms
title Adopting Artificial Intelligence in Public Healthcare: The Effect of Social Power and Learning Algorithms
title_full Adopting Artificial Intelligence in Public Healthcare: The Effect of Social Power and Learning Algorithms
title_fullStr Adopting Artificial Intelligence in Public Healthcare: The Effect of Social Power and Learning Algorithms
title_full_unstemmed Adopting Artificial Intelligence in Public Healthcare: The Effect of Social Power and Learning Algorithms
title_short Adopting Artificial Intelligence in Public Healthcare: The Effect of Social Power and Learning Algorithms
title_sort adopting artificial intelligence in public healthcare: the effect of social power and learning algorithms
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8656642/
https://www.ncbi.nlm.nih.gov/pubmed/34886404
http://dx.doi.org/10.3390/ijerph182312682
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