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Efforts to mitigate data diversity challenges in medical AI include the targeted inclusion of underrepresented conditions and populations, and benchmarking on globally diverse datasets to assess generalizability, as reported by Chen et al. (2024), Matos et al. (2024), and Group (2023).

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