Diversity, inclusivity and traceability of mammography datasets used in development of Artificial Intelligence technologies: a systematic review

Abstract

Through this review, we demonstrate gaps in the data landscape for mammography, highlighting poor representation globally. To ensure datasets in breast imaging have maximum utility for researchers, their characteristics should be documented and limitations of datasets, such as their representativeness of populations and settings, should inform scientific efforts to translate data-driven insights into technologies and discoveries.

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