Artificial neural network classification based on high-performance liquid chromatography of urinary and serum nucleosides for the clinical diagnosis of cancer

被引:68
作者
Yang, J [1 ]
Xu, GW [1 ]
Kong, HW [1 ]
Zheng, WF [1 ]
Pang, T [1 ]
Yang, Q [1 ]
机构
[1] Chinese Acad Sci, Dalian Inst Chem Phys, Natl Chromatog R&A, Dalian 116012, Peoples R China
来源
JOURNAL OF CHROMATOGRAPHY B-ANALYTICAL TECHNOLOGIES IN THE BIOMEDICAL AND LIFE SCIENCES | 2002年 / 780卷 / 01期
关键词
artificial neural networks; principal component analysis; nucleosides;
D O I
10.1016/S1570-0232(02)00408-7
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Nucleosides in human urine and serum have frequently been studied as a possible biomedical marker for cancer, acquired immune deficiency syndrome (AIDS) and the whole-body turnover of RNAs. Fifteen normal and modified nucleosides were determined in 69 urine and 42 serum samples using high-performance liquid chromatography (HPLC). Artificial neural networks have been used as a powerful pattern recognition tool to distinguish cancer patients from healthy persons. The recognition rate for the training set reached 100%. In the validating set, 95.8 and 92.9% of people were correctly classified into cancer patients and healthy persons when urine and serum were used as the sample for measuring the nucleosides. The results show that the artificial neural network technique is better than principal component analysis for the classification of healthy persons and cancer patients based on nucleoside data. (C) 2002 Elsevier Science B.V. All rights reserved.
引用
收藏
页码:27 / 33
页数:7
相关论文
共 27 条
[1]  
BEHRKE CW, 1990, CHROMATOGRAPHY MOD C
[2]  
Dong SY, 2000, CHINESE J ANAL CHEM, V28, P1025
[3]   Classification of single particles by neural networks based on the computer-controlled scanning electron microscopy data [J].
Hopke, PK ;
Song, XH .
ANALYTICA CHIMICA ACTA, 1997, 348 (1-3) :375-388
[4]   Prediction of electrophoretic mobilities of sulfonamides in capillary zone electrophoresis using artificial neural networks [J].
Jalali-Heravi, M ;
Garkani-Nejad, Z .
JOURNAL OF CHROMATOGRAPHY A, 2001, 927 (1-2) :211-218
[5]   Artificial neural network modeling of Kovats retention indices for noncyclic and monocyclic terpenes [J].
Jalali-Heravi, M ;
Fatemi, MH .
JOURNAL OF CHROMATOGRAPHY A, 2001, 915 (1-2) :177-183
[6]   Identification of multiple analytes using an optical sensor array and pattern recognition neural networks [J].
Johnson, SR ;
Sutter, JM ;
Engelhardt, HL ;
Jurs, PC ;
White, J ;
Kauer, JS ;
Dickinson, TA ;
Walt, DR .
ANALYTICAL CHEMISTRY, 1997, 69 (22) :4641-4648
[7]   Quantitation of urinary nucleosides by high-performance liquid chromatography [J].
Liebich, HM ;
DiStefano, C ;
Wixforth, A ;
Schmid, HR .
JOURNAL OF CHROMATOGRAPHY A, 1997, 763 (1-2) :193-197
[8]   Independent neural network modeling of class analogy for classification pattern recognition and optimization [J].
Liu, HL ;
Cao, XW ;
Xu, RJ ;
Chen, NY .
ANALYTICA CHIMICA ACTA, 1997, 342 (2-3) :223-228
[9]   Stabilization and speedup of convergence in training feedforward neural networks [J].
Looney, CG .
NEUROCOMPUTING, 1996, 10 (01) :7-31
[10]   APPLICATION OF PATTERN-RECOGNITION AND FEATURE EXTRACTION TECHNIQUES TO VOLATILE CONSTITUENT METABOLIC PROFILES OBTAINED BY CAPILLARY GAS-CHROMATOGRAPHY [J].
MCCONNELL, ML ;
RHODES, G ;
WATSON, U ;
NOVOTNY, M .
JOURNAL OF CHROMATOGRAPHY, 1979, 162 (04) :495-506