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Disparities in clinical studies of AI enabled applications from a global perspective.
Yang, Rui; Nair, Sabarinath Vinod; Ke, Yuhe; D'Agostino, Danny; Liu, Mingxuan; Ning, Yilin; Liu, Nan.
Afiliação
  • Yang R; Centre for Quantitative Medicine, Duke-NUS Medical School, Singapore, Singapore.
  • Nair SV; Centre for Quantitative Medicine, Duke-NUS Medical School, Singapore, Singapore.
  • Ke Y; Centre for Quantitative Medicine, Duke-NUS Medical School, Singapore, Singapore.
  • D'Agostino D; Department of Anesthesiology, Singapore General Hospital, Singapore, Singapore.
  • Liu M; Centre for Quantitative Medicine, Duke-NUS Medical School, Singapore, Singapore.
  • Ning Y; Centre for Quantitative Medicine, Duke-NUS Medical School, Singapore, Singapore.
  • Liu N; Centre for Quantitative Medicine, Duke-NUS Medical School, Singapore, Singapore.
NPJ Digit Med ; 7(1): 209, 2024 Aug 10.
Article em En | MEDLINE | ID: mdl-39127820
ABSTRACT
Artificial intelligence (AI) has been extensively researched in medicine, but its practical application remains limited. Meanwhile, there are various disparities in existing AI-enabled clinical studies, which pose a challenge to global health equity. In this study, we conducted an in-depth analysis of the geo-economic distribution of 159 AI-enabled clinical studies, as well as the gender disparities among these studies. We aim to reveal these disparities from a global literature perspective, thus highlighting the need for equitable access to medical AI technologies.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: NPJ Digit Med Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Singapura País de publicação: Reino Unido

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: NPJ Digit Med Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Singapura País de publicação: Reino Unido