Artificial neural network classification based on high-performance liquid chromatography of urinary and serum nucleosides for the clinical diagnosis of cancer
Artificial neural network classification based on high-performance liquid chromatography of urinary and serum nucleosides for the clinical diagnosis of cancer
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DOI：
10.1016/s1570-0232(02)00408-7
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发表时间：
2002-11-15
影响因子：
3
通讯作者：
Yang, Q
中科院分区：
文献类型：
--
作者：
Yang, J;Xu, GW;Yang, Q
人体尿液和血清中的核苷经常被作为癌症、获得性免疫缺陷综合征(AIDS)和RNA全身更新的可能生物医学标志而被研究。用高效液相色谱法测定了69份尿样和42份血清样品中15种核苷的含量。人工神经网络已成为区分癌症患者和健康人的一种强有力的模式识别工具。训练集的识别率达到100%。在验证组中，以尿和血清为样本测定核苷时，分别有95.8%和92.9%的人被正确区分为癌症患者和健康人。结果表明，对于基于核苷数据的健康人和癌症患者的分类，人工神经网络技术优于主成分分析。(C)2002 Elsevier Science B.V.保留所有权利。
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.