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Disease-medicine topic model for prescription record mining | IEEE Conference Publication | IEEE Xplore

Disease-medicine topic model for prescription record mining


Abstract:

Analyzing patient records is important for improving the quality of medical services and for understanding each patient's historical diseases. However, the huge size of t...Show More

Abstract:

Analyzing patient records is important for improving the quality of medical services and for understanding each patient's historical diseases. However, the huge size of the data requires statistical analysis procedures. In this paper, we proposed a probabilistic model-the disease-medicine topic model (DMTM)-to explore connected knowledge about diseases and medicines. In the model, diseases and medicines are modeled using generative process. We used the latent Dirichlet allocation, which is one of the most popular topic models, as the baseline model. Then, we compared the qualities of topic representations quantitatively and qualitatively. The comparison results showed that the topics derived from the DMTM are clearer to identify and that specific patterns were found in the diseases and medicines. In the case of topic network analysis, these specific patterns were proved using centrality measurements.
Date of Conference: 05-08 October 2014
Date Added to IEEE Xplore: 04 December 2014
Electronic ISBN:978-1-4799-3840-7
Print ISSN: 1062-922X
Conference Location: San Diego, CA, USA

References

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