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The inclusion of augmented intelligence in medicine: A framework for successful implementation.
Bazoukis, George; Hall, Jennifer; Loscalzo, Joseph; Antman, Elliott Marshall; Fuster, Valentín; Armoundas, Antonis A.
Afiliação
  • Bazoukis G; University of Nicosia, Medical School, Nicosia, Cyprus.
  • Hall J; American Heart Association, National Center, Dallas, TX.
  • Loscalzo J; Division of Cardiology, Department of Medicine, University of Minnesota, MN.
  • Antman EM; Department of Medicine, Brigham and Women's Hospital, Boston, MA.
  • Fuster V; Department of Medicine, Brigham and Women's Hospital, Boston, MA.
  • Armoundas AA; Cardiovascular Institute, Icahn School of Medicine at Mount Sinai, New York, New York.
Cell Rep Med ; 3(1): 100485, 2022 01 18.
Article em En | MEDLINE | ID: mdl-35106506
ABSTRACT
Artificial intelligence (AI) algorithms are being applied across a large spectrum of everyday life activities. The implementation of AI algorithms in clinical practice has been met with some skepticism and concern, mainly because of the uneasiness that stems, in part, from a lack of understanding of how AI operates, together with the role of physicians and patients in the decision-making process; uncertainties regarding the reliability of the data and the outcomes; as well as concerns regarding the transparency, accountability, liability, handling of personal data, and monitoring and system upgrades. In this viewpoint, we take these issues into consideration and offer an integrated regulatory framework to AI developers, clinicians, researchers, and regulators, aiming to facilitate the adoption of AI that rests within the FDA's pathway, in research, development, and clinical medicine.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Inteligência Artificial / Medicina Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: Cell Rep Med Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Inteligência Artificial / Medicina Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: Cell Rep Med Ano de publicação: 2022 Tipo de documento: Article