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공지사항
| 논문명 |
DIABETES THERAPY PROGNOSIS THROUGH DATA STREAM MINING METHODS AND TECHNIQUES |
| 구분 |
국제발표 |
| 저자 |
Dana Wang, Simon Fong, Seoungjae Cho, Kyungeun Cho, and Yongwoon Park |
| 국내/국외 |
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| 학술회의명 |
BIOMEDICAL ENGINEERING 2016 |
| 개최국가 |
Austria |
| 주관기관 |
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| 게재일 |
2016.11 |
| 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. |
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