使用锚词的生存监督主题建模：表征胰腺炎结局
Survival-Supervised Topic Modeling with Anchor Words: Characterizing Pancreatitis Outcomes
摘要：
我们介绍了一种新的主题建模方法，是监督生存分析。具体来说，我们建立在最近的工作无监督的主题建模与所谓的锚词提供监督通过弹性网络正则化考克斯比例风险模型。简而言之，锚词出现在文档中提供了文档部分关于特定主题的强烈指示。例如，通过在文档中看到“胆结石”，我们相当确定该文档部分与医学有关。我们所提出的方法交替学习主题模型和学习生存模型，以找到块凸优化问题的局部最小值。我们应用我们提出的方法来预测入住重症监护室（ICU）的胰腺炎患者将在ICU停留多长时间。我们的方法与各种基线中最好的一样准确，同时比任何基线都更易于解释。
英文摘要：
We introduce a new approach for topic modeling that is supervised by survival analysis. Specifically, we build on recent work on unsupervised topic modeling with so-called anchor words by providing supervision through an elastic-net regularized Cox proportional hazards model. In short, an anchor word being present in a document provides strong indication that the document is partially about a specific topic. For example, by seeing "gallstones" in a document, we are fairly certain that the document is partially about medicine. Our proposed method alternates between learning a topic model and learning a survival model to find a local minimum of a block convex optimization problem. We apply our proposed approach to predicting how long patients with pancreatitis admitted to an intensive care unit (ICU) will stay in the ICU. Our approach is as accurate as the best of a variety of baselines while being more interpretable than any of the baselines.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
