Deep learning facilitates the diagnosis of adult asthma.

Journal: Allergology international : official journal of the Japanese Society of Allergology
Published Date: May 30, 2019

Abstract

BACKGROUND: We explored whether the use of deep learning to model combinations of symptom-physical signs and objective tests, such as lung function tests and the bronchial challenge test, would improve model performance in predicting the initial diagnosis of adult asthma when compared to the conventional machine learning diagnostic method.

Authors

  • Katsuyuki Tomita
    Department of Respiratory Medicine, Yonago Medical Centre, Tottori, Japan. Electronic address: ktomita0223@gmail.com.
  • Ryota Nagao
    Department of Respiratory Medicine, Yonago Medical Centre, Tottori, Japan.
  • Hirokazu Touge
    Department of Respiratory Medicine, Yonago Medical Centre, Tottori, Japan.
  • Tomoyuki Ikeuchi
    Department of Respiratory Medicine, Yonago Medical Centre, Tottori, Japan.
  • Hiroyuki Sano
    Department of Respiratory Medicine and Allergology, Kindai University Faculty of Medicine, Osaka, Japan.
  • Akira Yamasaki
    Division of Medical Oncology and Molecular Respirology, Department of Multidisciplinary Internal Medicine, School of Medicine, Tottori University Faculty of Medicine, Tottori, Japan.
  • Yuji Tohda
    Department of Respiratory Medicine and Allergology, Kindai University Faculty of Medicine, Osaka, Japan.

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