The glomerular filtration rate (GFR) is an important index of renal function with advantages of accurate, sensitive, stable, repetitive and accurate measurement of renal functions. The GFR is mainly determined in the clear rate of radioisotope markers (99m)Tc-DTPA, the process of which is complicated, long time-taking, high cost, and radioactively injuring. Recently, the methods using other renal function parameters measured easily to create the mathematic models and to estimate GFR are being investigated in the world. In this paper, for the renal function data of the Chinese, the efficiency in the three existing GFR formulas has been optimized with multi-function optimization techniques and the accuracy of the computation has been improved. Then the BP neural network technology is used for establishing a new GFR formula, which is a simpler form and obtains higher precision result than the formulas existed. The rmse and P30 of the new formula are better than those of the old ones.
Algorithms ; Creatinine ; blood ; Cystatin C ; blood ; Glomerular Filtration Rate ; Humans ; Models, Theoretical ; Neural Networks (Computer) ; Technetium Tc 99m Pentetate