Genetics by genetic algorithm: Defining an ideal platelet donor population to support patients with <scp>HLA</scp> ‐mediated alloimmune refractoriness

While Pareto-optimal allocation enhances overall efficiency, targeted trade-offs, focusing on underrepresented groups, are essential to correct persistent disparities and achieve equitable HLA-matched platelet availability.

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Publication Details

Journal
Transfusion
Published
2025-10-08
DOI
https://doi.org/10.1111/trf.18446
Citations
1
Primary Topic
Blood groups and transfusion
Type
article
Field-Weighted Citation Impact
1.77
Controls
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article

Genetics by genetic algorithm: Defining an ideal platelet donor population to support patients with HLA ‐mediated alloimmune refractoriness

Matthew D. Seftel, J. Thomas Blake, Judith A. Mack, Natasha Rickards et al.
1 citations
Transfusion
Blood groups and transfusion
1.77
article

Genetics by genetic algorithm: Defining an ideal platelet donor population to support patients with HLA ‐mediated alloimmune refractoriness

Matthew D. Seftel, J. Thomas Blake, Judith A. Mack, Natasha Rickards, Aditya Kumar Gupta
article en
1 citations

Abstract

While Pareto-optimal allocation enhances overall efficiency, targeted trade-offs, focusing on underrepresented groups, are essential to correct persistent disparities and achieve equitable HLA-matched platelet availability.

TransfusionVol. 65(12)
Dalhousie University (CA), University of British Columbia (CA), University of Toronto (CA), McGill University (CA), Canadian Blood Services (CA)
Openalex Percentile: Top 12%
Blood groups and transfusion
1.77
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Genetics by genetic algorithm: Defining an ideal platelet donor population to support patients with <scp>HLA</scp> ‐mediated alloimmune refractoriness — Matthew D. Seftel, J. Thomas Blake, et al. · Transfusion (2025) | TGRS Research Map | TGRS