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Artificial Intelligence and Cancer Control: Toward Prioritizing Justice, Equity, Diversity, and Inclusion (JEDI) in Emerging Decision Support Technologies.
Taber, Peter; Armin, Julie S; Orozco, Gabriela; Del Fiol, Guilherme; Erdrich, Jennifer; Kawamoto, Kensaku; Israni, Sonoo Thadaney.
Afiliação
  • Taber P; Department of Biomedical Informatics, University of Utah School of Medicine, 421 Wakara Way, Salt Lake City, UT, 84108, USA. peter.taber@hsc.utah.edu.
  • Armin JS; Department of Family and Community Medicine, University of Arizona College of Medicine, Tucson, AZ, USA.
  • Orozco G; University of Arizona College of Medicine, Tucson, AZ, USA.
  • Del Fiol G; Department of Biomedical Informatics, University of Utah School of Medicine, 421 Wakara Way, Salt Lake City, UT, 84108, USA.
  • Erdrich J; Division of Surgical Oncology, University of Arizona College of Medicine, Tucson, AZ, USA.
  • Kawamoto K; Department of Biomedical Informatics, University of Utah School of Medicine, 421 Wakara Way, Salt Lake City, UT, 84108, USA.
  • Israni ST; Presence Center, Stanford University School of Medicine, Palo Alto, CA, USA.
Curr Oncol Rep ; 25(5): 387-424, 2023 05.
Article em En | MEDLINE | ID: mdl-36811808
ABSTRACT
PURPOSE FOR REVIEW This perspective piece has two goals first, to describe issues related to artificial intelligence-based applications for cancer control as they may impact health inequities or disparities; and second, to report on a review of systematic reviews and meta-analyses of artificial intelligence-based tools for cancer control to ascertain the extent to which discussions of justice, equity, diversity, inclusion, or health disparities manifest in syntheses of the field's best evidence. RECENT

FINDINGS:

We found that, while a significant proportion of existing syntheses of research on AI-based tools in cancer control use formal bias assessment tools, the fairness or equitability of models is not yet systematically analyzable across studies. Issues related to real-world use of AI-based tools for cancer control, such as workflow considerations, measures of usability and acceptance, or tool architecture, are more visible in the literature, but still addressed only in a minority of reviews. Artificial intelligence is poised to bring significant benefits to a wide range of applications in cancer control, but more thorough and standardized evaluations and reporting of model fairness are required to build the evidence base for AI-based tool design for cancer and to ensure that these emerging technologies promote equitable healthcare.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Inteligência Artificial / Diversidade, Equidade, Inclusão Tipo de estudo: Prognostic_studies / Systematic_reviews Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Inteligência Artificial / Diversidade, Equidade, Inclusão Tipo de estudo: Prognostic_studies / Systematic_reviews Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article