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Finding Hidden Relationships Between Medical Concepts by Leveraging Metamap and Text Mining Techniques

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Advanced Data Mining and Applications (ADMA 2022)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13725))

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Abstract

Text is one of the most common ways to store data in this computerized world. At a glance, it may seem that those data are not interconnected. But in reality, data can have hidden connections. Therefore, in this research, a new model has been presented that can find hidden relationships between two medical concepts by using MetaMap and appropriate text-mining techniques. Specifically, the model creates a new comprehensive index structure and can find cross-document hidden links connecting topics of interest that most existing approaches have ignored. Experiments show the effectiveness of the proposed model in discovering new connections between topics.

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Correspondence to Wei Jin .

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Yang, W., Chowdhury, S.M.M.H., Jin, W. (2022). Finding Hidden Relationships Between Medical Concepts by Leveraging Metamap and Text Mining Techniques. In: Chen, W., Yao, L., Cai, T., Pan, S., Shen, T., Li, X. (eds) Advanced Data Mining and Applications. ADMA 2022. Lecture Notes in Computer Science(), vol 13725. Springer, Cham. https://doi.org/10.1007/978-3-031-22064-7_4

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  • DOI: https://doi.org/10.1007/978-3-031-22064-7_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-22063-0

  • Online ISBN: 978-3-031-22064-7

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