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The Use of Deep Learning to Predict Stroke Patient Mortality

Author

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  • Songhee Cheon

    (Department of Physical Therapy, Youngsan University, Yangsan 626-790, Korea)

  • Jungyoon Kim

    (Department of Computer Science, Kent State University, Kent, OH 44242, USA)

  • Jihye Lim

    (Department of Healthcare Management, Youngsan University, Yangsan 626-790, Korea)

Abstract

The increase in stroke incidence with the aging of the Korean population will rapidly impose an economic burden on society. Timely treatment can improve stroke prognosis. Awareness of stroke warning signs and appropriate actions in the event of a stroke improve outcomes. Medical service use and health behavior data are easier to collect than medical imaging data. Here, we used a deep neural network to detect stroke using medical service use and health behavior data; we identified 15,099 patients with stroke. Principal component analysis (PCA) featuring quantile scaling was used to extract relevant background features from medical records; we used these to predict stroke. We compared our method (a scaled PCA/deep neural network [DNN] approach) to five other machine-learning methods. The area under the curve (AUC) value of our method was 83.48%; hence; it can be used by both patients and doctors to prescreen for possible stroke.

Suggested Citation

  • Songhee Cheon & Jungyoon Kim & Jihye Lim, 2019. "The Use of Deep Learning to Predict Stroke Patient Mortality," IJERPH, MDPI, vol. 16(11), pages 1-12, May.
    • Handle: RePEc:gam:jijerp:v:16:y:2019:i:11:p:1876-:d:234850
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    References listed on IDEAS

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    Cited by:

    1. Jungyoon Kim & Jihye Lim, 2021. "A Deep Neural Network-Based Method for Prediction of Dementia Using Big Data," IJERPH, MDPI, vol. 18(10), pages 1-13, May.
    2. María Carmen Lea-Pereira & Laura Amaya-Pascasio & Patricia Martínez-Sánchez & María del Mar Rodríguez Salvador & José Galván-Espinosa & Luis Téllez-Ramírez & Fernando Reche-Lorite & María-José Sánchez, 2022. "Predictive Model and Mortality Risk Score during Admission for Ischaemic Stroke with Conservative Treatment," IJERPH, MDPI, vol. 19(6), pages 1-16, March.

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