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An Effective Approach of Measuring Disease Similarities Based on the DNN Regression Model

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Intelligent Computing Theories and Application (ICIC 2019)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11644))

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Abstract

A large number of biomedical ontologies are created to provide controlled vocabularies for sharing biomedical knowledge in different biomedical domains. Quantitative measurement of disease associations based on biomedical ontologies could provide supports for discovering similar diseases caused by similar molecular process, which is beneficial to improve the corresponding medical diagnosis and treatment. Therefore, we deal with the effective measure of disease similarities in this paper. In particular, we propose a novel regression model based on the deep neural network (DNN) to improve the evaluation of similarities among diseases. We firstly extract the feature vectors of disease pairs, and then train the DNN-based regression model that learns from the information of training set to simulate the complex non-linear relationship among disease pairs. Finally, a comprehensive experimental evaluation is carried out to show the advantages as a solution for measuring disease similarities in terms of the receiver operating characteristic curve (ROC) and the precision-recall curve (PRC).

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Acknowledgements

The authors thank the anonymous referees for their valuable comments and suggestions. The work was partially supported by the National Key R&D Program of China (2018YFC1603800, 2018YFC1603802, 2017YFC1200200 and 2017YFC1200205), National Natural Science Foundation of China (61602130 and 61872115), China Postdoctoral Science Foundation funded project (2015M581449 and 2016T90294), Heilongjiang Postdoctoral Fund (LBH-Z14089), Natural Science Foundation of Heilongjiang Province of China (QC2015067), and Fundamental Research Funds for the Central Universities (HIT.NSRIF.2017036).

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Authors and Affiliations

  1. School of Computer Science and Technology, Harbin Institute of Technology, Harbin, 150001, China

    Shuhui Su & Jian Liu

  2. Changsha Medical University, Changsha, 410219, China

    Xiaoxiao(X.X.) Zhang

  3. Zhejiang University of Science and Technology, Hangzhou, 310023, China

    Lei Zhang

Authors
  1. Shuhui Su
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  2. Xiaoxiao(X.X.) Zhang
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  3. Lei Zhang
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  4. Jian Liu
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Corresponding author

Correspondence to Jian Liu .

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Editors and Affiliations

  1. Tongji University, Shanghai, China

    De-Shuang Huang

  2. University of Ulsan, Ulsan, Korea (Republic of)

    Kang-Hyun Jo

  3. Nanchang Institute of Technology, Nanchang, China

    Zhi-Kai Huang

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Su, S., Zhang, X., Zhang, L., Liu, J. (2019). An Effective Approach of Measuring Disease Similarities Based on the DNN Regression Model. In: Huang, DS., Jo, KH., Huang, ZK. (eds) Intelligent Computing Theories and Application. ICIC 2019. Lecture Notes in Computer Science(), vol 11644. Springer, Cham. https://doi.org/10.1007/978-3-030-26969-2_19

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  • DOI: https://doi.org/10.1007/978-3-030-26969-2_19

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-26968-5

  • Online ISBN: 978-3-030-26969-2

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