NDLI: Two researchers share how their cross disciplinary collaboration enables work to guide the future of data science.

Content Provider	Europe PMC
Author	Delano, Maggie Albert, Kendra
Copyright Year	2022
Abstract	In their recent perspective published in Patterns, 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.
Related Links	https://europepmc.org/backend/ptpmcrender.fcgi?accid=PMC9403352&blobtype=pdf
Journal	Patterns [Patterns (N Y)]
Volume Number	3
DOI	10.1016/j.patter.2022.100573
PubMed Central reference number	PMC9403352
Issue Number	8
PubMed reference number	36033588
e-ISSN	26663899
Language	English
Publisher	Elsevier
Publisher Date	2022-08-12
Access Restriction	Open
Rights License	This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). © 2022 The Author(s)
Content Type	Text
Resource Type	Article
Subject	Decision Sciences

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Two researchers share how their cross disciplinary collaboration enables work to guide the future of data science.