Sex trouble: Sex/gender slippage, sex confusion, and sex obsession in machine learning using electronic health records

Albert, Kendra; Delano, Maggie

doi:10.1016/j.patter.2022.100534

Cited by 8 publications

(2 citation statements)

References 81 publications

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“… 48 Nonetheless, evidence suggests that structured SOGI data collection still does not occur a majority of the time 49 and that conflation of sex- and gender-related terminology remains common. 50 The assessment of intersex status is often overlooked entirely.…”

Section: A Chain Of Conflation: How Inaccurate Data Collection and Re...mentioning

confidence: 99%

Queering genomics: How cisnormativity undermines genomic science

Jamal,

Zayhowski,

Berro

et al. 2024

Human Genetics and Genomics Advances

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Section: A Chain Of Conflation: How Inaccurate Data Collection and Re...mentioning

confidence: 99%

Queering genomics: How cisnormativity undermines genomic science

Jamal,

Zayhowski,

Berro

et al. 2024

Human Genetics and Genomics Advances

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“…I also have a background in gender studies and inclusive engineering design, which were particularly relevant for our recent paper published in Patterns . 1 During the pandemic, I started working with a group of researchers on human subjects testing for adversarial machine learning applications, leveraging what I had learned about testing biomedical devices. We learned a lot about where the machine learning field was with respect to testing and validation, which was part of the inspiration for the current paper we wrote.…”

Section: Main Textmentioning

confidence: 99%

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

Delano

Albert²

2022

Patterns

Self Cite

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Conducting inclusive research in genetics for transgender, gender‐diverse, and sex‐diverse individuals: Case analyses and recommendations from a clinical genomics study

Bland,

Gilmore,

Andujar

et al. 2023

Journal of Genetic Counseling

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A person's phenotypic sex (i.e., endogenous expression of primary, secondary, and endocrinological sex characteristics) can impact crucial aspects of genetic assessment and resulting clinical care recommendations. In studies with genetics components, it is critical to collect phenotypic sex, information about current organ/tissue inventory and hormonal milieu, and gender identity. If researchers do not carefully construct data models, transgender, gender diverse, and sex diverse (TGSD) individuals may be given inappropriate care recommendations and/or be subjected to misgendering, inflicting medical and psychosocial harms. The recognized need for an inclusive care experience should not be limited to clinical practice but should extend to the research setting, where researchers must build an inclusive experience for TGSD participants. Here, we review three TGSD participants in the Family History and Cancer Risk Study (FOREST) to critically evaluate sex‐ and gender‐related survey measures and associated data models in a study seeking to identify patients at risk for hereditary cancer syndromes. Furthermore, we leverage these participants' responses to sex‐ and gender identity‐related questions in FOREST to inform needed changes to the FOREST data model and to make recommendations for TGSD‐inclusive genetics research design, data models, and processes.

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Sex trouble: Sex/gender slippage, sex confusion, and sex obsession in machine learning using electronic health records

Cited by 8 publications

References 81 publications

Queering genomics: How cisnormativity undermines genomic science

Queering genomics: How cisnormativity undermines genomic science

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

Conducting inclusive research in genetics for transgender, gender‐diverse, and sex‐diverse individuals: Case analyses and recommendations from a clinical genomics study

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