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Equitable Health Intelligence: An Open Benchmark of Multi-Population Machine Learning for Omics-Based Cancer Prognosis

2026-06-02

Abstract excerpt

<h4>ABSTRACT</h4> <h4>Purpose</h4> Machine learning (ML) models for omics-based cancer prognosis are often trained on data from predominantly European-ancestry populations, producing biased predictions for other populations and undermining equitable genomic medicine. Existing fairness benchmarks mainly focus on outcome parity rather than predictive performance parity across populations. Public benchmark resource...

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Literature Corpus work
a04dd6e3-0a24-5de0-b425-baddcf514603
DOI
10.64898/2026.05.29.728755
Open publication

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Equitable Health Intelligence: An Open Benchmark of Multi-Population Machine Learning for Omics-Based Cancer PrognosisDOI 10.64898/2026.05.29.728755
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