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Imaging Artificial Intelligence: A Framework for Radiologists to Address Health Equity, From the AJR Special Series on DEI.
Davis, Melissa A; Lim, Nicholas; Jordan, John; Yee, Judy; Gichoya, Judy Wawira; Lee, Ryan.
Afiliação
  • Davis MA; Department of Diagnostic Radiology, Yale University School of Medicine, 789 Howard Ave, PO Box 20842, New Haven, CT 06520.
  • Lim N; Jefferson Health, Philadelphia, PA.
  • Jordan J; Stanford University School of Medicine, Stanford, CA.
  • Yee J; Montefiore Medical Center, Albert Einstein College of Medicine, New York, NY.
  • Gichoya JW; Department of Biology, Emory University, Atlanta, GA.
  • Lee R; Jefferson Health, Philadelphia, PA.
AJR Am J Roentgenol ; 221(3): 302-308, 2023 09.
Article em En | MEDLINE | ID: mdl-37095660
Artificial intelligence (AI) holds promise for helping patients access new and individualized health care pathways while increasing efficiencies for health care practitioners. Radiology has been at the forefront of this technology in medicine; many radiology practices are implementing and trialing AI-focused products. AI also holds great promise for reducing health disparities and promoting health equity. Radiology is ideally positioned to help reduce disparities given its central and critical role in patient care. The purposes of this article are to discuss the potential benefits and pitfalls of deploying AI algorithms in radiology, specifically highlighting the impact of AI on health equity; to explore ways to mitigate drivers of inequity; and to enhance pathways for creating better health care for all individuals, centering on a practical framework that helps radiologists address health equity during deployment of new tools.
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Texto completo: 1 Coleções: 01-internacional Contexto em Saúde: 11_ODS3_cobertura_universal / 1_ASSA2030 Base de dados: MEDLINE Assunto principal: Radiologia / Equidade em Saúde Tipo de estudo: Guideline Aspecto: Equity_inequality Limite: Humans Idioma: En Revista: AJR Am J Roentgenol Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Contexto em Saúde: 11_ODS3_cobertura_universal / 1_ASSA2030 Base de dados: MEDLINE Assunto principal: Radiologia / Equidade em Saúde Tipo de estudo: Guideline Aspecto: Equity_inequality Limite: Humans Idioma: En Revista: AJR Am J Roentgenol Ano de publicação: 2023 Tipo de documento: Article