Comparative Study among MAPE, RMSE and R Square Over the Treatment Techniques undergone for PCOS Influenced Women

Abstract

Among the various statistical measures, Root Mean Square Error (RMSE), Mean absolute Percentage Error (MAPE), and R-squared (Coefficient of determination) are the most widely used methods. The significance of the R square approach in the medical field was extensively discussed in the current review. Furthermore, we compared a number of statistical metrics for potential applications in the treatment of various disorders. In addition, the pertinent patents of R square for the consequences of testosterone and the enzymes aspartate dehydrogenase (AST) and alanine transaminase (ALT) on Polycystic Ovary Syndrome (PCOS) treated patients have been developed. We study in this paper the detailed comparative study on the biological system using RMSE, MAPE, and R Squared, which consists of 29 PCOS-influenced women against 20 healthy women and followed by the obesity verification model over the Sprague Dawley rats. R Square provides the best results among all mathematical regression analytical methods in PCOS-influenced patients. In this study, we provide the strong conclusion that aspartate dehydrogenase (AST) with testosterone treated on PCOS influenced women to have a greater chance of getting affected by Non-alcoholic fatty liver disease (NAFLD) rather than alanine transaminase (ALT) with testosterone- treated patients. Furthermore, this study extends their mathematical regression analysis through R squared for the obesity verification over rat model. It confirms that letrozole-treated rats are inhibited in obese compared with control rats, which results in a chance of NAFLD. Therefore, AST combined with testosterone creates a major chance for liver dysfunction.