Objective(s): To measure serum C-reactive protein (CRP) titer as a predictive diagnosis of acute hepatitis C virus (HCV)
infection.
Methodology: Two hundred and ten patients with acute HCV infection and 234 apparently healthy individuals as
control group were enrolled in this study in Baghdad medical city (Teaching Laboratories). The patents include
74(35.2%) females and 136 (64.8%) males with mean age (27±16.5) years. The control group includes 114 (48.7%)
females and 120 (51.3%) males with mean age (26±5.8) years. Blood samples were collected from out patients from
Alfadul in Baghdad city. Sera were separated and stored at 20 0
C. The diagnosis of acute HCV infection was based on
detection of HC Ag and anti- HCV IgM and standard liver function tests. Determination of CRP titer was assessed by
semi-quantitative tube agglutination test. All data were statistically analyzed.
Results: Based on 95% percentile, the baseline CRP titer in healthy individuals was 1:8 (16mg/l) and for patients 1:512
(1024mg/l). There was a statistically significant increase in the mean CRP titer in patients with acute HCV infection
compared to healthy individuals (P< 0.001) .The validly of CRP titer 1: 64 as a cut –off value to predict HCV infection
provide a sensitivity and specificity of 100 % and 96% respectively. Furthermore, there was a significant correlation
between CRP titer and liver function test values.
Recommendation:
Therefore, in further studies, we recommends the evaluation of C- reactive protein titer in patients with acute
hepatitis B Virus infection and patients with non–infectious diseases such as cardiovascular disease, diabetes mellitus
and hyperlipidemia infection, and compare between them.
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It is well known that the rate of penetration is a key function for drilling engineers since it is directly related to the final well cost, thus reducing the non-productive time is a target of interest for all oil companies by optimizing the drilling processes or drilling parameters. These drilling parameters include mechanical (RPM, WOB, flow rate, SPP, torque and hook load) and travel transit time. The big challenge prediction is the complex interconnection between the drilling parameters so artificial intelligence techniques have been conducted in this study to predict ROP using operational drilling parameters and formation characteristics. In the current study, three AI techniques have been used which are neural network, fuzzy i
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Machine learning is considered a powerful technique in many applications such as classification, clustering, recognition and prediction. Deep learning is a modern, vital and superior machine learning that gives stunning performance, especially with huge data. Stock market price prediction is the process of determining the future value of a prospect of a financial instrument traded in the market, to gain a great profit a successful prediction must be conducted, in order to achieve that machine learning is used, in this article, two approaches are proposed to predict the stock market prices and movement using two datasets, the first approach employs two machine learning models (J48 & logistic regression) while the second approach based on rec
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