The Gender of Biomedical Data: Challenges for Personalised and Precision Medicine

Mirjam Pot; Wanda Spahl; Barbara Prainsack

doi:10.3366/soma.2019.0278

The Gender of Biomedical Data: Challenges for Personalised and Precision Medicine

Mirjam Pot (Corresponding author)
, Wanda Spahl
, Barbara Prainsack

Publications: Contribution to journal › Article › Peer Reviewed

Original language	English
Pages (from-to)	170-187
Number of pages	18
Journal	Somatechnics
Volume	9
Issue number	2-3
DOIs	https://doi.org/10.3366/soma.2019.0278
Publication status	Published - 1 Dec 2019

Funding

We are grateful to Brigitte Bargetz, Milena Bister, Katharina Kieslich, Puneet Kishor, Lukas Schl?gl, Hendrik Wagenaar, and the participants of the workshop on ?Digital Data(-fication)? (7 December 2018, University of Vienna) for helpful comments and discussions. The usual disclaimer applies.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Austrian Fields of Science 2012

504014 Gender studies
504020 Medical sociology

Keywords

Bias
Big data
Digital health
Gender
Health information
Personalised medicine
Precision medicine
POPULATION
gender
CHRONIC PAIN
BIAS
BARRIERS
health information
CARE
WOMEN
EXPERIENCES
digital health
DISCRIMINATION
bias
CLINICAL-TRIALS
personalised medicine
precision medicine
HEALTH
big data

Access to Document

10.3366/soma.2019.0278

Cite this

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title = "The Gender of Biomedical Data: Challenges for Personalised and Precision Medicine",

keywords = "Bias, Big data, Digital health, Gender, Health information, Personalised medicine, Precision medicine, POPULATION, gender, CHRONIC PAIN, BIAS, BARRIERS, health information, CARE, WOMEN, EXPERIENCES, digital health, DISCRIMINATION, bias, CLINICAL-TRIALS, personalised medicine, precision medicine, HEALTH, big data",

author = "Mirjam Pot and Wanda Spahl and Barbara Prainsack",

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AU - Pot, Mirjam

AU - Spahl, Wanda

AU - Prainsack, Barbara

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KW - CHRONIC PAIN

KW - BIAS

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KW - precision medicine

KW - HEALTH

KW - big data

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ER -

The Gender of Biomedical Data: Challenges for Personalised and Precision Medicine

Funding

UN SDGs

Austrian Fields of Science 2012

Keywords

Access to Document

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