Two researchers share how their cross disciplinary collaboration enables work to guide the future of data science.
expert_opinion · Level V
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- Record sourced from PubMed, PMID 36033588.
- Also identified by DOI 10.1016/j.patter.2022.100573 and PMC identifier 9403352.
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Abstract
In their recent perspective published in <i>Patterns</i>, Maggie Delano and Kendra Albert highlight the limitations of sex and gender data classification in health systems and show how this contributes to the marginalization of trans and non-binary individuals. They provide recommendations to improve incorporating gender data into healthcare algorithms. Here they discuss their collaboration and how it enabled this cross-disciplinary research.