A case study of the application of WEKA software to solve the problem of liver inflamation

Mapping Intimacies ◽

10.21203/rs.3.rs-464435/v1 ◽

2021 ◽

Author(s):

Željko Vujović

Keyword(s):

Hepatitis C Virus ◽

Hepatitis C ◽

Binary Classification ◽

Software Tool ◽

Data Set ◽

A Value ◽

Egyptian Patients ◽

Sensitivity Specificity ◽

Fold Cross Validation

Abstract The aim of this paper was to consider the reliability of the basic metrics of evaluation of classification models: accuracy, sensitivity, specificity and precision. The WEKA software tool was applied to the "Hepatitis C virus (HCV) for Egyptian patients dataset". The algorithms Bayesnet, Naivebayesh, Multilayer Perceptron, J48 and 10-fold cross validation were used in the study. The main results obtained are that, with all four algorithms in question, they achieved approximately the same accuracy of correctly classified specimens. BaiesNet - 22.96%, NaiveBaies - 26.14%, MultilaierPerceptron - 26.57% and J48 - 25.27%. Binary classification metrics - sensitivity, specificity and precision show very different values, depending on the intended class. Metric specificity, for all four algorithms, shows that a value that is in most of the range of possible values [0,1]. Metric sensitivity and precision, for all four algorithms, showed values that are in the lower part of the range of possible values [0,1]. The results of this study showed that WEKA software could not yet be considered as a relevant tool for the diagnosis of Hepatitis C Virus, on whose data set it was applied.

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Oral conditions in hepatitis C virus‐infected Egyptian patients: a case‐control study

Egyptian Dental Journal ◽

10.21608/edj.2020.40529.1224 ◽

2020 ◽

Vol 66 (4) ◽

pp. 2339-2344

Author(s):

Asmaa Al Shafey ◽

Eman Abd Al hady

Keyword(s):

Hepatitis C Virus ◽

Hepatitis C ◽

Case Control Study ◽

Case Control ◽

Egyptian Patients ◽

Oral Conditions ◽

Control Study

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Assessment of antisperm antibodies in a sample of Egyptian patients with hepatitis C virus infection

Andrologia ◽

10.1111/and.12664 ◽

2016 ◽

Vol 49 (5) ◽

pp. e12664 ◽

Cited By ~ 1

Author(s):

T. M. Hussein ◽

D. Elneily ◽

A. A. Eid ◽

H. Abou-ElKhier

Keyword(s):

Hepatitis C Virus ◽

Hepatitis C ◽

Virus Infection ◽

Antisperm Antibodies ◽

Hepatitis C Virus Infection ◽

Egyptian Patients

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IL‐28β gene polymorphism determines virological response to PEGylated interferon therapy in hepatitis C virus genotype 4 Egyptian patients

Journal of Cellular Biochemistry ◽

10.1002/jcb.28096 ◽

2018 ◽

Vol 120 (5) ◽

pp. 8154-8159 ◽

Cited By ~ 2

Author(s):

Nashwa El‐Khazragy ◽

Naglaa El Sayed ◽

Ahmed M. Salem ◽

Nahla S. Hassan ◽

Amal Tohamy Abdelmoeaz ◽

...

Keyword(s):

Hepatitis C Virus ◽

Hepatitis C ◽

Gene Polymorphism ◽

Virological Response ◽

Interferon Therapy ◽

Pegylated Interferon ◽

Virus Genotype ◽

Genotype 4 ◽

Egyptian Patients

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An Immune Signature Robustly Predicts Clinical Deterioration for Hepatitis C Virus-Related Early-Stage Cirrhosis Patients

Frontiers in Medicine ◽

10.3389/fmed.2021.716869 ◽

2021 ◽

Vol 8 ◽

Author(s):

Cheng Guo ◽

Chenglai Dong ◽

Junjie Zhang ◽

Rui Wang ◽

Zhe Wang ◽

...

Keyword(s):

Hepatitis C Virus ◽

Hepatitis C ◽

Early Stage ◽

Gene Set Enrichment Analysis ◽

Functional Enrichment ◽

Calibration Plot ◽

Prognostic Signature ◽

Data Set ◽

Immune Infiltration ◽

Immune Related Genes

Hepatitis C virus (HCV)-related cirrhosis leads to a heavy global burden of disease. Clinical risk stratification in HCV-related compensated cirrhosis remains a major challenge. Here, we aim to develop a signature comprised of immune-related genes to identify patients at high risk of progression and systematically analyze immune infiltration in HCV-related early-stage cirrhosis patients. Bioinformatics analysis was applied to identify immune-related genes and construct a prognostic signature in microarray data set. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses were conducted with the “clusterProfiler” R package. Besides, the single sample gene set enrichment analysis (ssGSEA) was used to quantify immune-related risk term abundance. The nomogram and calibrate were set up via the integration of the risk score and clinicopathological characteristics to assess the effectiveness of the prognostic signature. Finally, three genes were identified and were adopted to build an immune-related prognostic signature for HCV-related cirrhosis patients. The signature was proved to be an independent risk element for HCV-related cirrhosis patients. In addition, according to the time-dependent receiver operating characteristic (ROC) curves, nomogram, and calibration plot, the prognostic model could precisely forecast the survival rate at the first, fifth, and tenth year. Notably, functional enrichment analyses indicated that cytokine activity, chemokine activity, leukocyte migration and chemotaxis, chemokine signaling pathway and viral protein interaction with cytokine and cytokine receptor were involved in HCV-related cirrhosis progression. Moreover, ssGSEA analyses revealed fierce immune-inflammatory response mechanisms in HCV progress. Generally, our work developed a robust prognostic signature that can accurately predict the overall survival, Child-Pugh class progression, hepatic decompensation, and hepatocellular carcinoma (HCC) for HCV-related early-stage cirrhosis patients. Functional enrichment and further immune infiltration analyses systematically elucidated potential immune response mechanisms.

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