Analyzing the serum of hemodialysis patients with end-stage chronic kidney disease by means of the combination of SERS and machine learning

被引:24
作者
Bratchenko, Lyudmila A. [1 ]
Al-Sammarraie, Sahar Z. [1 ]
Tupikova, Elena N. [2 ]
Konovalova, Daria Y. [3 ]
Lebedev, Peter A. [3 ]
Zakharov, Valery P. [1 ]
Bratchenko, Ivan A. [1 ]
机构
[1] Samara Univ, Dept Laser & Biotech Syst, 34 Moskovskoe Shosse, Samara 443086, Russia
[2] Samara Univ, Dept Chem, 34 Moskovskoe Shosse, Samara 443086, Russia
[3] Samara State Med Univ, Dept Internal Med, 159 Tashkentskaya St, Samara 443095, Russia
基金
俄罗斯科学基金会;
关键词
ENHANCED RAMAN-SPECTROSCOPY; VARIABLE IMPORTANCE; BLOOD-PLASMA; NANOPARTICLES; CLASSIFICATION; UREA;
D O I
10.1364/BOE.455549
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
The aim of this paper is a multivariate analysis of SERS characteristics of serum in hemodialysis patients, which includes constructing classification models (PLS-DA, CNN) by the presence/absence of end-stage chronic kidney disease (CKD) with dialysis and determining the most informative spectral bands for identifying dialysis patients by variable importance distribution. We found the spectral bands that are informative for detecting the hemodialysis patients: the 641 cm-1, 724 cm-1, 1094 cm-1 and 1393 cm-1 bands are associated with the degree of kidney function inhibition; and the 1001 cm-1 band is able to demonstrate the distinctive features of hemodialysis patients with end-stage CKD.
引用
收藏
页码:4926 / 4938
页数:13
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