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Artificial intelligence education: An evidence-based medicine approach for consumers, translators, and developers
Current and future healthcare professionals are generally not trained to cope with the proliferation of artificial intelligence (AI) technology in healthcare. To design a curriculum that caters to variable baseline knowledge and skills, clinicians may be conceptualized as “consumers”, “translators”,...
Autores principales: | Ng, Faye Yu Ci, Thirunavukarasu, Arun James, Cheng, Haoran, Tan, Ting Fang, Gutierrez, Laura, Lan, Yanyan, Ong, Jasmine Chiat Ling, Chong, Yap Seng, Ngiam, Kee Yuan, Ho, Dean, Wong, Tien Yin, Kwek, Kenneth, Doshi-Velez, Finale, Lucey, Catherine, Coffman, Thomas, Ting, Daniel Shu Wei |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10591047/ https://www.ncbi.nlm.nih.gov/pubmed/37852174 http://dx.doi.org/10.1016/j.xcrm.2023.101230 |
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