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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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0초록
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 algorithms; Data stream mining; Diabetes therapy; Insulin mellitus
- 제목
- Diabetes therapy prognosis through data stream mining methods and techniques
- 저자
- Wang, D.; Fong, S.; Cho, S.; Cho, K.; Park, Y.W.
- 발행일
- 2016
- 유형
- Conference Paper
- 저널명
- Proceedings of the 12th IASTED International Conference on Biomedical Engineering, BioMed 2016
- 페이지
- 127 ~ 132