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Optical screening of hepatitis-B infected blood sera using optical technique and neural network classifier

机译:利用光学技术和神经网络分类器对乙型肝炎感染的血液进行光学筛查

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摘要

In this study we demonstrate the analysis of biochemical changes in the human blood sera infected with Hepatitis B virus (HBV) using Raman spectroscopy. In total, 120 diseased blood samples and 170 healthy blood samples, collected from Pakistan Atomic Energy Commission (PAEC) general hospital, were analyzed. Spectra from each sample of both groups were collected in the spectral range 400-1700 cm(-1). Careful spectral analyses demonstrated significant spectral variations (p < 0.0001) in the HBV infected individuals as compared to the normal ones. The spectral variations presumably occur because of the variations in the concentration of important biomolecules. Variations in spectral signatures were further exploited by using a neural network classifier towards machine-assisted classification of the two groups. Evaluation metrics of the classifier showed the diagnostic accuracy of (0.993), sensitivity ( = 0.992), specificity ( = 0.994), positive predictive value ( = 0.992) and negative predictive value ( = 0.994). The observed variations in the molecular concentration may be important markers of the hepatic performance and can be used in the diagnosis and machine-assisted classification of HBV infection.
机译:在这项研究中,我们证明了使用拉曼光谱法分析感染了乙型肝炎病毒(HBV)的人血血清中的生化变化。总共分析了从巴基斯坦原子能委员会(PAEC)总医院收集的120例患病血液样本和170例健康血液样本。两组的每个样品的光谱都在400-1700 cm(-1)的光谱范围内收集。仔细的光谱分析表明,与正常人相比,HBV感染者有明显的光谱变化(p <0.0001)。可能由于重要生物分子浓度的变化而发生光谱变化。通过使用神经网络分类器对两组进行机器辅助分类,可以进一步利用光谱特征的变化。分类器的评估指标显示诊断准确性为(0.993),敏感性(= 0.992),特异性(= 0.994),阳性预测值(= 0.992)和阴性预测值(= 0.994)。观察到的分子浓度变化可能是肝功能的重要标志,可用于HBV感染的诊断和机器辅助分类。

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