[2005.08146] Semi-Automating Knowledge Base Construction for Cancer Geneticsopen searchopen navigation menucontact arXivarXiv Twitter

In this work, we consider the exponentially growing subarea of genetics in cancer. The need to synthesize and centralize this evidence for dissemination has motivated a team of physicians to manually construct and maintain a knowledge base that distills key results reported in the literature. This is a laborious process that entails reading through full-text articles to understand the study design, assess study quality, and extract the reported cancer risk estimates associated with particular hereditary cancer genes (i.e., penetrance). In this work, we propose models to automatically surface key elements from full-text cancer genetics articles, with the ultimate aim of expediting the manual workflow currently in place. We propose two challenging tasks that are critical for characterizing the findings reported cancer genetics studies: (i) Extracting snippets of text that describe \emph{ascertainment mechanisms}, which in turn inform whether the population studied may introduce bias ow

1 mentions: @byron_c_wallace
Date: 2020/05/19 18:52

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@byron_c_wallace New work led by @SominW on semi-automating knowledge base construction for cancer genetics: t.co/1Kzacvx3cO. #AKBC 2020 w/Mass General Hospital collaborators (Kevin Hughes and @yinkanhua) t.co/m3B7s8M2uz

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