University of Florida researchers have introduced PhyloFrame in Nature Communications—a framework that addresses key gaps in precision medicine by mitigating ancestral bias. Like fine-tuning an instrument, this method recalibrates predictive models to capture diverse genomic signatures. Consider exploring its application in cancer subtyping to enhance diagnostic fairness and accuracy in healthcare.

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Equitable machine learning counteracts ancestral bias in precision medicine