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Authors
Lehmann, Brieuc https://orcid.org/0000-0002-7302-4391
Bräuninger, Leandra https://orcid.org/0009-0005-5137-0217
Cho, Yoonsu
Falck, Fabian
Jayadeva, Smera
Katell, Michael
Nguyen, Thuy
Perini, Antonella
Tallman, Sam
Mackintosh, Maxine
Silver, Matt
Kuchenbäcker, Karoline
Leslie, David
Chatterjee, Nilanjan https://orcid.org/0000-0002-9060-008X
Holmes, Chris
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Article History
Accepted: 27 March 2025
First Online: 15 May 2025
Competing interests
: This manuscript was informed by a project commissioned by the Diverse Data (DD) initiative at Genomics England (GEL) in December 2022 to explore the use of statistical and machine learning methods to improve fairness and equity in genomics. K.K. is the Scientific Lead for DD. S.T., T.N. and Y.C. are Genomic Data Scientists at GEL. M.S. was the Lead Genomic Data Scientist for DD, and M.M. was the Programme Lead for DD. B.L. and L.B. were paid consultants to GEL for the project. M.M. is Director of One HealthTech, which provides the secretariat for the Data Science for Health Equity community, which B.L. is also the co-founder of. B.L. and L.B. have acted as consultants for Google DeepMind in relation to other research in this field; however, Google DeepMind was not involved in this project or this publication. F.F. is an employee and shareholder of Microsoft Corporation.
