Diabetes therapy prognosis through data stream mining methods and techniques

  • Wang, D.
  • Fong, S.
  • Cho, S.
  • Cho, K.
  • Park, Y.W.
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초록

Diabetes is one of the frequently occurring non-communicable diseases that lead causes of deaths among the worldwide. Maintain an appropriate blood glucose value for the patient needs a right amount of insulin dosage and the timing of its intake. But the medical interaction to the different lifestyle patients cause to the complexity of the therapy. In this article, a real-time classification therapy prognosis model is proposed to compute for regulating IDDM based on the daily prescription record and patients' individual blood glucose pattern by using data stream mining. A computer simulation is presented for evaluating the most appropriate data stream algorithms for this task.

키워드

Classification algorithmsData stream miningDiabetes therapyInsulin mellitus
제목
Diabetes therapy prognosis through data stream mining methods and techniques
저자
Wang, D.Fong, S.Cho, S.Cho, K.Park, Y.W.
DOI
10.2316/P.2016.832-066
발행일
2016
유형
Conference Paper
저널명
Proceedings of the 12th IASTED International Conference on Biomedical Engineering, BioMed 2016
페이지
127 ~ 132