基于肿瘤标志物数据多维分析的肺恶性肿瘤计算机辅助诊断

Q4 Agricultural and Biological Sciences Nova Biotechnologica et Chimica Pub Date : 2021-12-04 DOI:10.36547/nbc.1309
V. Mrázová, J. Mocák, E. Varmusová, Denisa Kavková
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引用次数: 0

摘要

这项工作的目的是评估肺部肿瘤标志物的诊断性能。三项临床实验室测试用于指示肺部恶性肿瘤,以验证或预测患者的诊断。对182名患者的数据集进行了检查,并创建了两组主要的患者样本——86名诊断为恶性肿瘤(经组织学证实),96名诊断为良性肿瘤或结核病。分析了以下肿瘤标志物:癌胚抗原和细胞角蛋白19片段,它们在胸膜渗出液中取样,以及血清中相同的肿瘤标志物。此外,患者的年龄和相应个体的性别被用作原始数据矩阵中的进一步变量。为了验证或预测患者的诊断,我们使用了三种实验室测试来指示肺部恶性肿瘤,不仅使用了所选的单个实验室测试的结果,还应用了多元统计方法,该方法以最佳线性组合的形式联合利用了所有进行的测试。
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Computer-aided diagnosis of lung malignity using multidimensional analysis of tumour marker data
The aim of this work is assessing diagnostic performance of lung tumour markers. Three clinical laboratory tests were used for indicating lung malignancy in order to verify or predict the patient’s diagnosis. The data set of 182 patients was examined and two main groups of the patient samples were created – 86 with diagnosed malignancy (confirmed by histology) and 96 with diagnosed benign tumours or tuberculosis. The following tumour markers were analyzed: carcinoembryonic antigen and cytokeratin 19 fragment, which were sampled in the pleural exudates, and the same tumour markers in serum. In addition, the patient’s age and the gender of the corresponding individual were used as further variables in the original data matrix. Three laboratory tests were used for indicating lung malignancy in order to verify or predict the patient’s diagnosis not only by using the results of the chosen individual laboratory test but also applying multivariate statistical approach, which jointly utilizes all performed tests in the form of their optimal linear combination.
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来源期刊
Nova Biotechnologica et Chimica
Nova Biotechnologica et Chimica Agricultural and Biological Sciences-Food Science
CiteScore
0.60
自引率
0.00%
发文量
47
审稿时长
24 weeks
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