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Accurate Prediction of Advanced Liver Fibrosis Using the Decision Tree Learning Algorithm in Chronic Hepatitis C Egyptian Patients

Background/Aim. Respectively with the prevalence of chronic hepatitis C in the world, using noninvasive methods as an alternative method in staging chronic liver diseases for avoiding the drawbacks of biopsy is significantly increasing. The aim of this study is to combine the serum biomarkers and clinical information to develop a classification model that can predict advanced liver fibrosis

Artificial Intelligence

Accurate harmonic phase tracking of tagged MRI using locally-uniform myocardium displacement constraint

Harmonic phase (HARP) tracking is one of the most commonly used techniques for estimating the myocardium regional function from tagged cardiac Magnetic Resonance Imaging sequences. Nevertheless, tag fading and phase distortion can severely limit the tracking accuracy of the technique. In this work, we propose to modify the HARP tracking algorithm to impose a constraint of locally uniform

Artificial Intelligence

NileTMRG at SemEval-2016 Task 7: Deriving prior polarities for Arabic sentiment terms

This paper presents a model that was developed to address SemEval Task 7: "Determining Sentiment Intensity of English and Arabic Phrases", with focus on 'Arabic Phrases'. The goal of this task is to determine the degree to which some given term is associated with positive sentiment. The underlying premise behind the model that we have adopted is that determining the context (positive or negative)

Artificial Intelligence

NileTMRG at SemEval-2016 task 5: Deep convolutional neural networks for aspect category and sentiment extraction

This paper describes our participation in the SemEval-2016 task 5, Aspect Based Sentiment Analysis (ABSA). We participated in two slots in the sentence level ABSA (Subtask 1) namely: aspect category extraction (Slot 1) and sentiment polarity extraction (Slot 3) in English Restaurants and Laptops reviews. For Slot 1, we applied different models for each domain. In the restaurants domain, we used an

Artificial Intelligence

Which configuration works best? an experimental study on supervised Arabic twitter sentiment analysis

Arabic Twitter Sentiment Analysis has been gaining a lot of attention lately with supervised approaches being exploited widely. However, to date, there has not been an experimental study that examines how different configurations of the Bag of Words model, text representation scheme, can affect various supervised machine learning methods. The goal of the presented work is to do exactly that

Artificial Intelligence

Early detection of hepatocellular carcinoma co-occurring with hepatitis C virus infection: A mathematical model

AIM: To develop a mathematical model for the early detection of hepatocellular carcinoma (HCC) with a panel of serum proteins in combination with α-fetoprotein (AFP). METHODS: Serum levels of interleukin (IL)-8, soluble intercellular adhesion molecule-1 (sICAM-1), soluble tumor necrosis factor receptor II (sTNF-R II), proteasome, and β-catenin were measured in 479 subjects categorized into four

Artificial Intelligence

Lightweight authentication protocol deployment over FlexRay

In-vehicle network security is becoming a major concern for the automotive industry. Although there is significant research done in this area, there is still a significant gap between research and what is actually applied in practice. Controller area network (CAN) gains the most concern of community but little attention is given to FlexRay. Many signs indicate the approaching end of CAN usage and

Artificial Intelligence

Assessing leanness level with demand dynamics in a multi-stage production system

Purpose - The purpose of this paper is to present a dynamic model to measure the degree of system's leanness under dynamic demand conditions using a novel integrated metric. Design/methodology/approach - The multi-stage production system model is based on a system dynamics approach. The leanness level is measured using a new developed integrated metric that combines efficiency,WIP performance as

Energy and Water
Circuit Theory and Applications
Software and Communications

Assessment of cardiac mass from tagged magnetic resonance images

Purpose: Tagged and cine magnetic resonance imaging (tMRI and cMRI) techniques are used for evaluating regional and global heart function, respectively. Measuring global function parameters directly from tMRI is challenging due to the obstruction of the anatomical structure by the tagging pattern. The purpose of this study was to develop a method for processing the tMRI images to improve the

Artificial Intelligence
Healthcare
Circuit Theory and Applications
Software and Communications

Synthesizable SVA protocol checker generation methodology based on TDML and VCD file formats

System Verilog Assertions (SVA) is widely used by hardware designers and verification engineers to apply Assertion Based Verification (ABV) methodology on their hardware designs. However, the complexity in understanding different protocol standards in general and JEDEC memory protocol standards in specific imposes numerous difficulties on designers and verification engineers when translating

Circuit Theory and Applications