Quantification of biomedical NMR data using artificial neural network analysis: Lipoprotein lipid profiles from H-1 NMR data of human plasma

被引:38
作者
AlaKorpela, M
Hiltunen, Y
Bell, JD
机构
[1] UNIV OULU, DEPT PHYS SCI, NMR RES GRP, SF-90571 OULU, FINLAND
[2] RAAHE INST COMP ENGN, PER BRAHE LAB, SF-92101 RAAHE, FINLAND
关键词
D O I
10.1002/nbm.1940080603
中图分类号
Q6 [生物物理学];
学科分类号
071011 ;
摘要
Artificial neural network (ANN) analysis is a new technique in NMR spectroscopy, It is very often considered only as an efficient 'black-box' tool for data classification, but we emphasize here that ANN analysis Is also powerful for data quantification, The possibility of finding out the biochemical rationale controlling the ANN outputs is presented and discussed, Furthermore, the characteristics of ANN analysis, as applied to plasma lipoprotein lipid quantification, are compared to those of sophisticated lineshave fitting (LF) analysis, The performance of LF in this particular application is shown to be less satisfactory when compared to neural networks, The lipoprotein lipid quantification represents a regular clinical need and serves as a good example of an NMR spectroscopic case of extreme signal overlap, The ANN analysis enables quantification of lipids in very low, intermediate, low and high density lipoprotein (VLDL, IDL, LDL and HDL, respectively) fractions directly from a H-1 NMR spectrum of a plasma sample in <1 h, The ANN extension presented is believed to increase the value of the H-1 NMR based lipoprotein quantification to the point that it could be the method of choice in some advanced research settings. Furthermore, the excellent quantification performance of the ANN analysis, demonstrated in this study, serves as an indication of the broad potential of neural networks in biomedical NMR.
引用
收藏
页码:235 / 244
页数:10
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