生命银行
可解释性
人口
医学
前瞻性队列研究
研究设计
数据科学
环境卫生
计算机科学
生物信息学
统计
生物
内科学
人工智能
数学
作者
Naomi E. Allen,Ben Lacey,Debbie A. Lawlor,Jill P. Pell,John Gallacher,Liam Smeeth,Paul Elliott,Paul M. Matthews,Ronan A Lyons,Anthony D. Whetton,Anneke Lucassen,Matthew E. Hurles,Michael Chapman,Andrew Roddam,Natalie Fitzpatrick,Anna Hansell,Rebecca Hardy,Riccardo E. Marioni,Valerie B. O’Donnell,Julie Williams
标识
DOI:10.1126/scitranslmed.adf4428
摘要
Population-based prospective studies, such as UK Biobank, are valuable for generating and testing hypotheses about the potential causes of human disease. We describe how UK Biobank’s study design, data access policies, and approaches to statistical analysis can help to minimize error and improve the interpretability of research findings, with implications for other population-based prospective studies being established worldwide.
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