Genetic Algorithm Based for Identification of Heart Disease Risk Factors
Main Article Content
The purpose of this thesis was to examine heart disease Angina risk factors. In particular, this Thesis was organized around the central theme of adiposity, which is a prevalent Complication following SCI. Study focused on understanding the relationships between activities of daily living (ADL) and risk factors including central adiposity, lipoproteins, and triglycerides. Using genetic algorithm, while controlling for pertinent covariates such as sex, age, and leisure time physical activity (LTPA), it was found that Mobility ADL (wheeling and transferring) were negatively associated with total and LDL-cholesterol. Study also examined whether individuals who considered themselves to be overweight subsequently had less favorable subjective well-being, and were more likely to report specific secondary complications than individuals who did not consider themselves to be overweight. In summary, the findings suggest that a) participation in specific types of ADL (i.e. Mobility ADL) are associated with a lower risk and should be further explored) elevated perceived adiposity is associated with specific secondary complications and lower subjective well-being. Overall thesis findings support the overwhelming evidence of the benefits of daily physical activity and maintaining a healthy bodyweight in the SCI population
How to Cite
, A. vashist, K. B. S. K. A. V. “Genetic Algorithm Based for Identification of Heart Disease Risk Factors”. International Journal on Recent and Innovation Trends in Computing and Communication, vol. 3, no. 5, May 2015, pp. 3099-03, doi:10.17762/ijritcc.v3i5.4399.