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| 1 | Metastatic renal cell carcinoma to the testis: a ease report and review of the literature 显示文摘 | Marzouk K Alyami F Merrimen J | 2014 | Can Urol Assoe J2014，，： | 1 |
| 2 | Epstein-Barr-virusinduced interstitial lung disease显示文摘 | Marzouk K Corate L Saleh S | 2005 | Curr Opin Pulm Med2005，11，： | 1 |
| 3 | Deep Learning Enabled Computer Aided Diagnosis Model for Lung Cancer using Biomedical CT Images显示文摘Early detection of lung cancer can help for improving the survival rate of the patients.Biomedical imaging tools such as computed tomography(CT)image was utilized to the proper identification and positioning of lung cancer.The recently developed deep learning(DL)models can be employed for the effectual identification and classification of diseases.This article introduces novel deep learning enabled CAD technique for lung cancer using biomedical CT image,named DLCADLC-BCT technique.The proposed DLCADLC-BCT technique intends for detecting and classifying lung cancer using CT images.The proposed DLCADLC-BCT technique initially uses gray level co-occurrence matrix(GLCM)model for feature extraction.Also,long short term memory(LSTM)model was applied for classifying the existence of lung cancer in the CT images.Moreover,moth swarm optimization(MSO)algorithm is employed to optimally choose the hyperparameters of the LSTM model such as learning rate,batch size,and epoch count.For demonstrating the improved classifier results of the DLCADLC-BCT approach,a set of simulations were executed on benchmark dataset and the outcomes exhibited the supremacy of the DLCADLC-BCT technique over the recent approaches. | Mohammad Alamgeer Hanan Abdullah Mengash Radwa Marzouk Mohamed K Nour Anwer Mustafa Hilal Abdelwahed Motwakel Abu Sarwar Zamani Mohammed Rizwanullah | 2022 | Computers, Materials & Continua2022，，10： | 1 |
| 4 | Body composition and resting energy expenditure in clinically stable,nonweight-losing patients with severe emphysema显示文摘 | Cohen RI Marzouk K Berkosi P | 2003 | Chest2003，124，： | 1 |
| 5 | Epstein-Barr-virus-induced interstitial lung disease 显示文摘 | Marzouk K Corate L Saleh S | 2005 | Curr Opin Pulm Med2005，11，5： | 1 |
| 6 | Effects of freezing and thawing on the tension properties of high-strength concrete 显示文摘 | Marzouk H K | 1995 | Materials Journal1995，91，6： | 1 |
| 7 | Epstein-Barr-virus-induced interstitial lung disease显示文摘 | Marzouk K Corate L Saleh S | 2005 | Curr Opin Pulm Med2005，11，5： | 1 |
| 8 | Anal Chem显示文摘 | Marzouk S A M Ashraf S S Tayyari K A | 2007 | 79(4):1668-16742007，79，4： | 1 |
| 9 | Body composition and rest- ing energy expenditure in clinically stable, non - weight losing pa- tients with severe emphysema 显示文摘 | Cohen RI Marzouk K Berkoski P | 2003 | Chest2003，124，4： | 1 |
| 10 | Evaluation of a simplifled IS6110 PCR for the rapid diagnosis of Mycobacterium tuberculosis in an area with high tuberculosis incidence显示文摘 | Ben K I Ben SW Marzouk M etal | 2009 | Pathol Biol2009，，： | 1 |
| 11 | Effects of freezing and thawing on the tension properties of high-strength concrete 显示文摘 | Marzouk H Jiang K | 1995 | ACI Materials Journal1995，91，6： | 1 |
| 12 | Effects of Freezing and Thawing on the Tension Properties of High-strength Concrete显示文摘 | MARZOUK H JIANG K | 1995 | ACI Materials Journal1995，91，6： | 1 |
| 13 | Renal effects of nitric oxide in endotoxemia显示文摘 | Cohen RI Hassell AM Marzouk K | 2001 | Am J Respir Crit Care Med2001，164，101： | 1 |
| 14 | Me- latonin levels in periodontal health and disease显示文摘 | Almughrabi O M Marzouk K M Hasanato R M | 2013 | J Periodon- tal Res2013，，48： | 1 |
| 15 | Epstein-Barr-virus-in-duced interstitial lung disease 显示文摘 | Marzouk K Corate L Saleh S | 2005 | Curr Opin Pulm Med2005，11，5： | 1 |
| 16 | A new flavone diglycoside from Carthamus tinctorius seeds显示文摘 | Ahmed K M Marzouk M S Wahab S A | 2000 | Pharmazie2000，55，8： | 1 |
| 17 | Improved Metaheuristics with Deep Learning Enabled Movie Review Sentiment Analysis显示文摘Sentiment Analysis(SA)of natural language text is not only a challenging process but also gains significance in various Natural Language Processing(NLP)applications.The SA is utilized in various applications,namely,education,to improve the learning and teaching processes,marketing strategies,customer trend predictions,and the stock market.Various researchers have applied lexicon-related approaches,Machine Learning(ML)techniques and so on to conduct the SA for multiple languages,for instance,English and Chinese.Due to the increased popularity of the Deep Learning models,the current study used diverse configuration settings of the Convolution Neural Network(CNN)model and conducted SA for Hindi movie reviews.The current study introduces an Effective Improved Metaheuristics with Deep Learning(DL)-Enabled Sentiment Analysis for Movie Reviews(IMDLSA-MR)model.The presented IMDLSA-MR technique initially applies different levels of pre-processing to convert the input data into a compatible format.Besides,the Term Frequency-Inverse Document Frequency(TF-IDF)model is exploited to generate the word vectors from the pre-processed data.The Deep Belief Network(DBN)model is utilized to analyse and classify the sentiments.Finally,the improved Jellyfish Search Optimization(IJSO)algorithm is utilized for optimal fine-tuning of the hyperparameters related to the DBN model,which shows the novelty of the work.Different experimental analyses were conducted to validate the better performance of the proposed IMDLSA-MR model.The comparative study outcomes highlighted the enhanced performance of the proposed IMDLSA-MR model over recent DL models with a maximum accuracy of 98.92%. | Abdelwahed Motwakel Najm Alotaibi Eatedal Alabdulkreem Hussain Alshahrani MohamedAhmed Elfaki Mohamed K Nour Radwa Marzouk Mahmoud Othman | 2023 | Computer Systems Science & Engineering2023，47，10： | 0 |
| 18 | Weather Forecasting Prediction Using Ensemble Machine Learning for Big Data Applications显示文摘The agricultural sector’s day-to-day operations,such as irrigation and sowing,are impacted by the weather.Therefore,weather constitutes a key role in all regular human activities.Weather forecasting must be accurate and precise to plan our activities and safeguard ourselves as well as our property from disasters.Rainfall,wind speed,humidity,wind direction,cloud,temperature,and other weather forecasting variables are used in this work for weather prediction.Many research works have been conducted on weather forecasting.The drawbacks of existing approaches are that they are less effective,inaccurate,and time-consuming.To overcome these issues,this paper proposes an enhanced and reliable weather forecasting technique.As well as developing weather forecasting in remote areas.Weather data analysis and machine learning techniques,such as Gradient Boosting Decision Tree,Random Forest,Naive Bayes Bernoulli,and KNN Algorithm are deployed to anticipate weather conditions.A comparative analysis of result outcome said in determining the number of ensemble methods that may be utilized to improve the accuracy of prediction in weather forecasting.The aim of this study is to demonstrate its ability to predict weather forecasts as soon as possible.Experimental evaluation shows our ensemble technique achieves 95%prediction accuracy.Also,for 1000 nodes it is less than 10 s for prediction,and for 5000 nodes it takes less than 40 s for prediction. | Hadil Shaiba Radwa Marzouk Mohamed K Nour Noha Negm Anwer Mustafa Hilal Abdullah Mohamed Abdelwahed Motwakel Ishfaq Yaseen Abu Sarwar Zamani Mohammed Rizwanullah | 2022 | Computers, Materials & Continua2022，，11： | 0 |
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