一种概率方法提取妊娠期糖尿病早期预测的定性知识。

Athresh Karanam, Alexander L Hayes, Harsha Kokel, David M Haas, Predrag Radivojac, Sriraam Natarajan
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引用次数: 2

摘要

定性影响陈述通常是先验的,以指导学习;我们回答了一个具有挑战性的反向任务,并从一个学习概率模型中自动提取它们。我们将我们的定性知识提取方法应用于临床研究数据的早期预测。实证结果表明,所提取的规则具有可解释性和有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Probabilistic Approach to Extract Qualitative Knowledge for Early Prediction of Gestational Diabetes.

Qualitative influence statements are often provided a priori to guide learning; we answer a challenging reverse task and automatically extract them from a learned probabilistic model. We apply our Qualitative Knowledge Extraction method toward early prediction of gestational diabetes on clinical study data. Our empirical results demonstrate that the extracted rules are both interpretable and valid.

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