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Journal of Tsinghua University(Science and Technology)    2019, Vol. 59 Issue (3) : 169-177     DOI: 10.16511/j.cnki.qhdxxb.2018.25.050
COMPUTER SCIENCE AND TECHNOLOGY |
Representation learning approach for medical activities enhanced by topical modeling
XU Xiao, WANG Ying, JIN Tao, WANG Jianmin
School of Software, Tsinghua University, Beijing 100084, China
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Abstract  With the explosion of the amount of medical data, data-driven medical analyses are receiving increasing attention. Proper representation of medical activities is crucial for such analyses. However, most existing representations are designed without considering the temporality and numerical sensitivity of medical data, which limits the performance and interpretability of the analysis tasks. This paper presents a representation learning approach for medical activities that is enhanced by topical modeling for inpatient data. The approach leverages the temporal relations between activities and the topic assignment to construct a multilayer perceptron model. Evaluations using large real data sets demonstrate that this approach significantly improves three typical medical analysis tasks, while providing medical interpretations.
Keywords representation learning      topic modeling      multilayer perceptron      medical analyses     
Corresponding Authors: 金涛,助理研究员,E-mail:jintao05@gmail.com     E-mail: jintao05@gmail.com
Issue Date: 19 March 2019
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XU Xiao
WANG Ying
JIN Tao
WANG Jianmin
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XU Xiao,WANG Ying,JIN Tao, et al. Representation learning approach for medical activities enhanced by topical modeling[J]. Journal of Tsinghua University(Science and Technology), 2019, 59(3): 169-177.
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http://jst.tsinghuajournals.com/EN/10.16511/j.cnki.qhdxxb.2018.25.050     OR     http://jst.tsinghuajournals.com/EN/Y2019/V59/I3/169
  
  
  
  
  
  
  
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