Development of Type 2 Diabetes Mellitus Phenotyping Framework Using Expert Knowledge and Machine Learning Approach.

Journal: Journal of diabetes science and technology
Published Date: Dec 7, 2016

Abstract

BACKGROUND: Phenotyping is an automated technique that can be used to distinguish patients based on electronic health records. To improve the quality of medical care and advance type 2 diabetes mellitus (T2DM) research, the demand for T2DM phenotyping has been increasing. Some existing phenotyping algorithms are not sufficiently accurate for screening or identifying clinical research subjects.

Authors

  • Rina Kagawa
    1 Department of Biomedical Informatics, Graduate School of Medicine, The University of Tokyo, Bunkyo-ku, Tokyo, Japan.
  • Yoshimasa Kawazoe
    Department of Biomedical Informatics, Graduate School of Medicine, The University of Tokyo, Bunkyo-ku, Tokyo, Japan.
  • Yusuke Ida
    2 Department of Healthcare Information Management, The University of Tokyo Hospital, Bunkyo-ku, Tokyo, Japan.
  • Emiko Shinohara
    The University of Tokyo Hospital, Tokyo, Japan.
  • Katsuya Tanaka
    1 Department of Biomedical Informatics, Graduate School of Medicine, The University of Tokyo, Bunkyo-ku, Tokyo, Japan.
  • Takeshi Imai
    Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
  • Kazuhiko Ohe
    Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.

Keywords

External Resources

Popular Topics
Recent Journals