Fairness of machine learning classifiers in medical image analysis

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Fairness of machine learning classifiers in medical image analysis

Medical institutions around the world are adopting machine learning (ML) systems to assist in analyzing health data; at the same time, the fairness research community has shown that ML systems can be biased, resulting in disparate performance for specific subpopulations. In this talk, we will discuss the relationship between bias, ML and health systems, addressing the specific case of gender bias in X-ray classifiers for computer-assisted diagnosis.

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