Neural network technology to predict intracellular water volume

J. S. Chiu, C. A. Chen, C. H. Lee, Y. C. Li, Y. F. Lin, Y. F. Wang, Fu Chiu Yu

研究成果: 雜誌貢獻文章同行評審

1 引文 斯高帕斯(Scopus)


Artificial neural network (ANN) is increasingly applied in clinical medicine. We therefore constructed an ANN to predict intracellular water (ICW) volume in 44 healthy Taiwaners. Demographic and anthropometric data were recorded as predictors, and ICW volume measured by bioelectrical impedance analysis (ICW-BIA) was the reference. ICW volume predicted by ANN (ICW-ANN) was compared with ICW-BIA. ICW-BIA (21.26 ± 0.58l) and ICW-ANN (21.25 ± 0.57l) was insignificantly different (p = 0.76). ICW-BIA and ICW-ANN were strongly correlated (r = 0.94, p <0.0001) with a significant agreement (mean difference, 0.01; lower and upper limits of agreement, -2.31 and 2.33) in Bland-Altman plot. Passing-Bablok regression was described as ICW-BIA = 1.04 × ICW-ANN-0.49, with 95% confidence interval for slope 0.94-1.14 and for intercept -2.76-1.49, indicating that both methods were interchangeable. ANN provided an excellent alternative of BIA to predict ICW volume in healthy subjects.

頁(從 - 到)1231-1238
期刊International Journal of Clinical Practice
出版狀態已發佈 - 10月 2006

ASJC Scopus subject areas

  • 醫藥 (全部)


深入研究「Neural network technology to predict intracellular water volume」主題。共同形成了獨特的指紋。