妇女健康数据科学的挑战与机遇。

IF 7 Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Todd L Edwards, Catherine A Greene, Jacqueline A Piekos, Jacklyn N Hellwege, Gabrielle Hampton, Elizabeth A Jasper, Digna R Velez Edwards
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引用次数: 0

摘要

女性健康与数据科学的交叉研究是一个历来落后于其他领域的研究领域,但最近却获得了强劲的发展势头。推动这一增长的原因不仅有新的研究人员进入这一领域,还有数据科学的新方法、新资源和新技术带来的巨大机遇。在此,我们将介绍当今妇女健康研究人员为应对生物医学数据科学挑战而使用的一些资源和方法。我们还介绍了应用这些方法促进妇女健康成果的机会和局限性,以及该领域的未来,重点是将现有方法重新用于妇女健康。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Challenges and Opportunities for Data Science in Women's Health.

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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来源期刊
CiteScore
11.10
自引率
1.70%
发文量
0
期刊介绍: The Annual Review of Biomedical Data Science provides comprehensive expert reviews in biomedical data science, focusing on advanced methods to store, retrieve, analyze, and organize biomedical data and knowledge. The scope of the journal encompasses informatics, computational, artificial intelligence (AI), and statistical approaches to biomedical data, including the sub-fields of bioinformatics, computational biology, biomedical informatics, clinical and clinical research informatics, biostatistics, and imaging informatics. The mission of the journal is to identify both emerging and established areas of biomedical data science, and the leaders in these fields.
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