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Prediction of Onset of Lifestyle-Related Diseases Using Regular Health Checkup Data

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Advances in Artificial Intelligence (JSAI 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1128))

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Abstract

This is an extension from a selected paper from JSAI2019. This study proposes a method to predict the onset of lifestyle-related diseases using periodical health checkup data. In this study, we carefully examine insurance claims data to identify onset of diseases and use the data for supervised learning. We aim to predict whether lifestyle-related diseases, except cancer, will develop within a year. We adopt the undersampling and bagging approach to address the class imbalance problem. The precision and recall of the proposed method are found to be 0.32 and 0.89, respectively. Compared with a baseline that sets thresholds for each examination item and considers their logical sum, our method achieves much higher precision while maintaining the recall; this allows suppression of the number of targets for health guidance, without increasingly neglecting those who are likely to become severely ill.

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Notes

  1. 1.

    https://www.ningen-dock.jp/wp/wp-content/uploads/2013/09/Dock-Hantei2018-20181214.pdf.

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Author information

Authors and Affiliations

  1. Kyoto Institute of Technology, Matsugasaki, Sakyo-ku, Kyoto, Japan

    Mitsuru Tsunekawa, Natsuki Oka & Masahiro Araki

  2. SG Holdings Group Health Insurance Association, 637, Suiginnya-cho, Shimogyo-ku, Kyoto, Japan

    Motoshi Shintani

  3. Japan System Techniques Co., Ltd., 2-3-18, Nakanoshima, Kita-ku, Osaka, Japan

    Masataka Yoshikawa

  4. Juntendo University, 2-1-1, Hongo, Bunkyo-ku, Tokyo, Japan

    Takeshi Tanigawa

Authors
  1. Mitsuru Tsunekawa
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  2. Natsuki Oka
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  3. Masahiro Araki
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  4. Motoshi Shintani
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  5. Masataka Yoshikawa
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  6. Takeshi Tanigawa
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Corresponding author

Correspondence to Mitsuru Tsunekawa .

Editor information

Editors and Affiliations

  1. Department of Systems Innovation, University of Tokyo, Tokyo, Japan

    Yukio Ohsawa

  2. Faculty of Business and Commerce, Kansai University, Osaka, Japan

    Katsutoshi Yada

  3. Nagoya Institute of Technology, Nagoya, Japan

    Takayuki Ito

  4. Graduate School of System Design, Tokyo Metropolitan University, Tokyo, Japan

    Yasufumi Takama

  5. Department of Information and Communication, Tokyo Metropolitan University, Tokyo, Japan

    Eri Sato-Shimokawara

  6. Faculty of Letters, Chiba University, Chiba, Japan

    Akinori Abe

  7. School of Engineering, The University of Tokyo, Tokyo, Japan

    Junichiro Mori

  8. Graduate School of Economics, Osaka University, Toyonaka, Osaka, Japan

    Naohiro Matsumura

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Tsunekawa, M., Oka, N., Araki, M., Shintani, M., Yoshikawa, M., Tanigawa, T. (2020). Prediction of Onset of Lifestyle-Related Diseases Using Regular Health Checkup Data. In: Ohsawa, Y., et al. Advances in Artificial Intelligence. JSAI 2019. Advances in Intelligent Systems and Computing, vol 1128. Springer, Cham. https://doi.org/10.1007/978-3-030-39878-1_2

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