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A Prediction Model of Gestational Diabetes Mellitus Based on First Pregnancy Test Index

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Health Information Science (HIS 2020)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12435))

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Abstract

The purpose of this study is to discuss the possibility of predicting gestational diabetes mellitus (GDM) by analyzing the first test indexes. In order to verify the prediction effect, we used 61 indexes, including age and 60 test indexes, from December 2015 to May 2018 in Beijing Pinggu District Hospital, and conducted experiments of GDM risk prediction based on a variety of different models, ranged from LR, LDA, RF to XGBoost. The experimental results reveal that compared to the dataset of using major relevant indicators, the dataset of using full indicators performs better. Besides, logistic regression can achieve a relatively good prediction effect. On the test set of all data, the area under the curve (AUC) of the Logistic regression model reaches 0.7787. In the meantime, the accuracy rate of the Logistic Regression model reaches (69.991 ± 2.833)%, and the recall rate and the mean value of the F1 value are (70.598 ± 2.210)% and (70.264 ± 2.128)%, respectively. So the analysis based on the first pregnancy test can play a role in predicting GDM to a certain extent.

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Authors and Affiliations

  1. Faculty of Information Technology, Beijing University of Technology, Beijing, 100124, China

    Jianzhuo Yan, Yanan Geng, Hongxia Xu, Yongchuan Yu, Sinuo Deng & Xiaoxue Du

  2. Engineering Research Center of Digital Community, Beijing University of Technology, Beijing, 100124, China

    Jianzhuo Yan, Yanan Geng, Hongxia Xu, Yongchuan Yu, Sinuo Deng & Xiaoxue Du

  3. Join Lab of Digital Health, Beijing University of Technology and Beijing Pinggu Hospital, Beijing, 100124, China

    Jianzhuo Yan, Yanan Geng, Hongxia Xu, Shaofeng Tan, Dongdong He, Sinuo Deng & Xiaoxue Du

  4. Information Center of Beijing Pinggu Hospital, Beijing, 101200, China

    Shaofeng Tan & Dongdong He

Authors
  1. Jianzhuo Yan
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  2. Yanan Geng
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  3. Hongxia Xu
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  4. Shaofeng Tan
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  5. Dongdong He
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  6. Yongchuan Yu
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  7. Sinuo Deng
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  8. Xiaoxue Du
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Corresponding author

Correspondence to Hongxia Xu .

Editor information

Editors and Affiliations

  1. Vrije University of Amsterdam, Amsterdam, The Netherlands

    Zhisheng Huang

  2. Victoria University, Footscray, VIC, Australia

    Siuly Siuly

  3. Victoria University, Footscray, VIC, Australia

    Hua Wang

  4. Swinburne University of Technology, Hawthorn, VIC, Australia

    Rui Zhou

  5. Victoria University, Footscray, VIC, Australia

    Yanchun Zhang

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Yan, J. et al. (2020). A Prediction Model of Gestational Diabetes Mellitus Based on First Pregnancy Test Index. In: Huang, Z., Siuly, S., Wang, H., Zhou, R., Zhang, Y. (eds) Health Information Science. HIS 2020. Lecture Notes in Computer Science(), vol 12435. Springer, Cham. https://doi.org/10.1007/978-3-030-61951-0_12

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  • DOI: https://doi.org/10.1007/978-3-030-61951-0_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-61950-3

  • Online ISBN: 978-3-030-61951-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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