A Probabilistic Approach to Extract Qualitative Knowledge for Early Prediction of Gestational Diabetes.

A Probabilistic Approach to Extract Qualitative Knowledge for Early Prediction of Gestational Diabetes.
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一种概率方法提取妊娠期糖尿病早期预测的定性知识。

DOI:
10.1007/978-3-030-77211-6_59
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发表时间:
2021-06
期刊:
Artificial intelligence in medicine. Conference on Artificial Intelligence in Medicine (2005- )
影响因子:
--
通讯作者:
Natarajan S
Natarajan S
中科院分区:
其他
文献类型:
--
作者:
Karanam A;Hayes AL;Kokel H;Haas DM;Radivojac P;Natarajan S

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定性影响陈述通常是先验提供的,以指导学习;我们回答一个具有挑战性的反向任务,并自动从学习的概率模型中提取它们。我们将我们的定性知识提取方法应用于临床研究数据对妊娠期糖尿病的早期预测。我们的实证结果表明,提取的规则是可解释的和有效的。
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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