Incidence Rate Prediction of Diabetes from Medical Checkup Data

• MORIMOTO Masakazu

  Graduate School of Engineering, University of Hyogo

• KAMIURA Naotake

  Graduate School of Engineering, University of Hyogo

• HATA Yutaka

  Graduate School of Simulation Studies, University of Hyogo

• YAMAMOTO Ichiro

  Himeji Medical Association

Abstract

To promote effective guidance by health checkup results, this paper predict a likelihood of developing lifestyle-related diseases from health check data. In this paper, we focus on the fluctuation of hemoglobin A1c (HbA1c) value, which deeply connected with diabetes onset. Here we predict incensement of HbA1c value and examine which kind of health checkup item has important role for HbA1c fluctuation. Our experimental results show that, when we classify the subjects according to their gender and triglyceride (TG) fluctuation value, we will effectively evaluate the risk of diabetes onset for each class.

Journal

• IEICE Transactions on Information and Systems

  IEICE Transactions on Information and Systems E100.D (8), 1642-1646, 2017

  The Institute of Electronics, Information and Communication Engineers

Keywords

• specific health examination
• lifestyle-related disease
• machine learning

Details

• CRID: 1390001204377414912
• NII Article ID: 130005876140
• DOI: 10.1587/transinf.2016lop0012
• ISSN: 17451361
• ISSN: 09168532
• Web Site: https://www.jstage.jst.go.jp/article/transinf/E100.D/8/E100.D_2016LOP0012/_pdf
• Text Lang: en
• Data Source:
  • JaLC
  • Crossref
  • CiNii Articles
• Abstract License Flag: Disallowed