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Artificial intelligence education: An evidence-based medicine approach for consumers, translators, and developers.
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.
Afiliação
  • Ng FYC; Artificial Intelligence and Digital Innovation, Singapore Eye Research Institute, Singapore National Eye Center, Singapore Health Service, Singapore, Singapore; Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
  • Thirunavukarasu AJ; Artificial Intelligence and Digital Innovation, Singapore Eye Research Institute, Singapore National Eye Center, Singapore Health Service, Singapore, Singapore; University of Cambridge School of Clinical Medicine, Cambridge, UK; Oxford University Clinical Academic Graduate School, University of Oxfo
  • Cheng H; Artificial Intelligence and Digital Innovation, Singapore Eye Research Institute, Singapore National Eye Center, Singapore Health Service, Singapore, Singapore; Rollins School of Public Health, Emory University, Atlanta, GA, USA; Duke-NUS Medical School, National University of Singapore, Singapore,
  • Tan TF; Artificial Intelligence and Digital Innovation, Singapore Eye Research Institute, Singapore National Eye Center, Singapore Health Service, Singapore, Singapore.
  • Gutierrez L; Artificial Intelligence and Digital Innovation, Singapore Eye Research Institute, Singapore National Eye Center, Singapore Health Service, Singapore, Singapore.
  • Lan Y; Institute for AI Industry Research (AIR), Tsinghua University, Beijing, China.
  • Ong JCL; Department of Pharmacy, Singapore General Hospital, Singapore, Singapore.
  • Chong YS; Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore; Dean's Office, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
  • Ngiam KY; Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore; Biomedical Engineering, School of Engineering, National University of Singapore, Singapore, Singapore.
  • Ho D; Biomedical Engineering, School of Engineering, National University of Singapore, Singapore, Singapore; Insitute for Digital Medicine (WisDM), N.1 Institute for Health, National University of Singapore, Singapore, Singapore; Department of Pharmacology, National University of Singapore, Singapore, Sin
  • Wong TY; Tsinghua Medicine, Tsinghua University, Beijing, China.
  • Kwek K; Chief Executive Office, Singapore General Hospital, SingHealth, Singapore, Singapore.
  • Doshi-Velez F; Harvard Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA.
  • Lucey C; Executive Vice Chancellor and Provost Office, University of California, San Francisco, San Francisco, CA, USA.
  • Coffman T; Duke-NUS Medical School, National University of Singapore, Singapore, Singapore.
  • Ting DSW; Artificial Intelligence and Digital Innovation, Singapore Eye Research Institute, Singapore National Eye Center, Singapore Health Service, Singapore, Singapore; Duke-NUS Medical School, National University of Singapore, Singapore, Singapore; Byers Eye Institute, Stanford University, Palo Alto, CA, U
Cell Rep Med ; 4(10): 101230, 2023 10 17.
Article em En | MEDLINE | ID: mdl-37852174
ABSTRACT
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", or "developers". The changes required of medical education because of AI innovation are linked to those brought about by evidence-based medicine (EBM). We outline a core curriculum for AI education of future consumers, translators, and developers, emphasizing the links between AI and EBM, with suggestions for how teaching may be integrated into existing curricula. We consider the key barriers to implementation of AI in the medical curriculum time, resources, variable interest, and knowledge retention. By improving AI literacy rates and fostering a translator- and developer-enriched workforce, innovation may be accelerated for the benefit of patients and practitioners.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Inteligência Artificial / Educação Médica Idioma: En Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Singapura

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Inteligência Artificial / Educação Médica Idioma: En Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Singapura