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Challenges and Opportunities for Data Science in Women's Health.
Edwards, Todd L; Greene, Catherine A; Piekos, Jacqueline A; Hellwege, Jacklyn N; Hampton, Gabrielle; Jasper, Elizabeth A; Velez Edwards, Digna R.
Afiliação
  • Edwards TL; Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
  • Greene CA; Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, Tennessee, USA; email: digna.r.velez.edwards@vumc.org.
  • Piekos JA; Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, Tennessee, USA; email: digna.r.velez.edwards@vumc.org.
  • Hellwege JN; Division of Quantitative Sciences, Department of Obstetrics and Gynecology, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
  • Hampton G; Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, Tennessee, USA; email: digna.r.velez.edwards@vumc.org.
  • Jasper EA; Division of Quantitative Sciences, Department of Obstetrics and Gynecology, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
  • Velez Edwards DR; Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, Tennessee, USA; email: digna.r.velez.edwards@vumc.org.
Annu Rev Biomed Data Sci ; 6: 23-45, 2023 08 10.
Article em En | MEDLINE | ID: mdl-37040736
ABSTRACT
The intersection of women's health and data science is a field of research that has historically trailed other fields, but more recently it has gained momentum. This growth is being driven not only by new investigators who are moving into this area but also by the significant opportunities that have emerged in new methodologies, resources, and technologies in data science. Here, we describe some of the resources and methods being used by women's health researchers today to meet challenges in biomedical data science. We also describe the opportunities and limitations of applying these approaches to advance women's health outcomes and the future of the field, with emphasis on repurposing existing methodologies for women's health.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Saúde da Mulher / Ciência de Dados Tipo de estudo: Prognostic_studies Limite: Female / Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Saúde da Mulher / Ciência de Dados Tipo de estudo: Prognostic_studies Limite: Female / Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article