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- W4205507973 abstract "Abstract How can we realize the potential of artificial intelligence and machine learning for addressing cancer inequities and advancing cancer health disparities research? This presentation will discuss areas where bias can be introduced into the AI and machine learning design, development, implementation, use and standardization for cancer care. What are the factors that contribute to bias in the research continuum and how can we mitigate them? The presentation will provide some promising and actionable examples of how we can leverage the transformative potential of AI and machine learning to address cancer health disparities. Citation Format: Irene Dankwa-Mullan. Leveraging the potential of artificial and machine learning technologies to address cancer health disparities [abstract]. In: Proceedings of the AACR Virtual Conference: 14th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2021 Oct 6-8. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2022;31(1 Suppl):Abstract nr IA-04." @default.
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- W4205507973 date "2022-01-01" @default.
- W4205507973 modified "2023-10-07" @default.
- W4205507973 title "Abstract IA-04: Leveraging the potential of artificial and machine learning technologies to address cancer health disparities" @default.
- W4205507973 doi "https://doi.org/10.1158/1538-7755.disp21-ia-04" @default.
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