识别与特定疾病相关的医学术语

2015 IEEE International Conference on Data Mining Workshop (ICDMW) Pub Date : 2015-11-14 DOI:10.1109/ICDMW.2015.71

Mihir Shekhar, Veera Raghavendra Chikka, Lini T. Thomas, Sunil Mandhan, K. Karlapalem

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引用次数: 3

摘要

我们提出了一个使用机器学习技术的自动疾病术语分类模型，该模型将医学术语分类到特定的疾病类别。我们研究五种特殊的疾病:癌症、艾滋病、关节炎、糖尿病和心脏病。我们识别和分类医学术语，如药物名称、症状、缩写、疾病名称、测试等，并将其归类到特定的疾病类别中。结果表明，我们的疾病术语分类模型发现所有疾病术语类别的平均f值为0.966。

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Identifying Medical Terms Related to Specific Diseases

We present an automated disease term classification model using machine learning techniques that classifies a medical term to a specific disease class. We work on five particular diseases: Cancer, AIDS, Arthritis, Diabetes and heart related ailments. We identify and classify medical terms like drug names, symptoms, abbreviations, disease names, tests, etc., into their specific diseases classes. The results illustrate that our model for disease term classification finds all disease term classes with an average F-score of 0.966.

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来源期刊

2015 IEEE International Conference on Data Mining Workshop (ICDMW)

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