Name
Title | ||
|---|---|---|
Risk factors rule mining in hypertension: Korean National Health and Nutrient Examinations Survey 2007–2014 |
Abstract | ||
|---|---|---|
The prevention of hypertension is one of the most important topics in health research. In the most of the previous studies used statistical methods for analyzing the association between hypertension prevalence and dietary. However, statistical methods have some limitation which are, it is difficult to interpret variables interaction at a time. Thus we apply the data mining techniques for generation of prognosis factors based on association rule mining. In our experiment, we conducted Korean National Health and Nutrient Examination Survey (KNHANES) data from 2007 to 2014. We used to filter-based feature selection method for find prognosis factors and we generate the rules based on discovered risk factors of prognosis in hypertension. We evaluated discovered rules by support and confidence. In the results shows that, we can find useful rules for prognosis of hypertension. We expected to support medical decision making and easy to interpret prognosis of hypertension. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/CIBCB.2016.7758128 | 2016 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB) |
Keywords | Field | DocType |
Association rule mining,Feature selection,Hypertension,Prognosis,KNHANES | Medical decision making,Feature selection,Computer science,Some limitation,Rule mining,Association rule learning,Bioinformatics | Conference |
ISBN | Citations | PageRank |
978-1-5090-0012-8 | 0 | 0.34 |
References | Authors | |
2 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hyun Woo Park | 1 | 12 | 5.15 |
| Erdenebileg Batbaatar | 2 | 0 | 0.34 |
| Dingkun Li | 3 | 1 | 3.07 |
| Keun Ho Ryu | 4 | 883 | 85.61 |