Obesity is a complex disease arising from an excessive accumula-tion of body fat which leads to various complications such as diabetes, hyper-tension, and renal diseases. The growing prevalence of obesity is also becom-ing a major risk factor for nephropathy. When patients are diagnosed with nephropathy, their progression towards renal failure is usually inevitable. Therefore, a prediction tool will help medical doctors identify patients with a higher risk of developing nephropathy and implement early treatment or pre-vention. In this study, we attempted to construct a diagnostic support system for nephropathy using clinical and genetic traits. Our results show that pre-diction models involving the use of both genetic and clinical features yielded the best classification performance. Our finding is in accordance with the complex nature of obesity-related nephropathy and support the notion of us-ing genetic traits to design a personalized diagnostic model.
Relation:
The 2nd International Workshop on Pattern Mining and Application of Big Data (BigPMA 2015) (in conjunction with PAKDD 2015)
