Name
Title | ||
|---|---|---|
Genetic Algorithm Based Methods for Identification of Health Risk Factors Aimed at Preventing Metabolic Syndrome |
Abstract | ||
|---|---|---|
In recent years, metabolic syndrome has emerged as a major health concern because it increases the risk of developing lifestyle diseases, such as diabetes, hypertension, and cardiovascular disease. Some of the symptoms of the metabolic syndrome are high blood pressure, decreased HDL cholesterol, and elevated triglycerides (TG). To prevent the developing of metabolic syndrome, accurate prediction of the future values of these health risk factors and identification of other factors from the health checkup and lifestyle data, which are highly related with these risk factors, are very important. In this paper, we propose a new framework, based on genetic algorithm and its variants, for identifying those important health factors and predicting the future health risk of a person with high accuracy. We show the effectiveness of the proposed system by applying it to the health checkup and lifestyle data of Toshiba Corporation. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1007/978-3-540-89694-4_22 | SEAL |
Keywords | Field | DocType |
health risk factor,lifestyle disease,important health factor,genetic algorithm,health checkup,lifestyle data,health risk,future health risk,preventing metabolic syndrome,future value,major health concern,metabolic syndrome,risk factor,risk factors | Health risk,Diabetes mellitus,Disease,Computer science,Intensive care medicine,Artificial intelligence,Blood pressure,Genetic algorithm,Machine learning,Metabolic syndrome,Decreased HDL cholesterol | Conference |
Volume | ISSN | Citations |
5361 | 0302-9743 | 1 |
PageRank | References | Authors |
0.40 | 6 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Topon Kumar | 1 | 73 | 5.07 |
| Ken Ueno | 2 | 124 | 13.27 |
| Koichiro Iwata | 3 | 10 | 1.74 |
| Toshio Hayashi | 4 | 10 | 1.74 |
| Nobuyoshi Honda | 5 | 10 | 1.74 |