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Lightweight Transfer Learning Models for Ultrasound-Guided Classification of COVID-19 Patients

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Computers, Materials & Continua 2021年第11期69卷 2295-2312页

作者： mohamed Esmail Karar Omar Reyad Mohammed Abd-Elnaby Abdel-Haleem Abdel-Aty marwa Ahmed Shouman College of Computing and Information Technology Shaqra UniversityShaqra11961Saudi Arabia Department of Industrial Electronics and Control Engineering Faculty of Electronic Engineering(FEE)Menoufia UniversityMenouf32952Egypt Department of Mathematics and Computer Science Faculty of ScienceSohag UniversitySohag82524Egypt Department of Computer Engineering College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Physics College of SciencesUniversity of BishaBisha61922Saudi Arabia Department of Physics Faculty of ScienceAl-Azhar UniversityAssiut71524Egypt Department of Computer Science and Engineering Faculty of Electronic Engineering(FEE)Menoufia UniversityMenouf32952Egypt

Lightweight deep convolutional neural networks(CNNs)present a good solution to achieve fast and accurate image-guided diagnostic procedures of COVID-19 ***,advantages of portable Ultrasound(US)imaging such as simplicity and safe procedures have attracted many radiologists for scanning suspected COVID-19 *** this paper,a new framework of lightweight deep learning classifiers,namely COVID-LWNet is proposed to identify COVID-19 and pneumonia abnormalities in US *** to traditional deep learning models,lightweight CNNs showed significant performance of real-time vision applications by using mobile devices with limited hardware *** main lightweight deep learning models,namely MobileNets,ShuffleNets,MENet and MnasNet have been proposed to identify the health status of lungs using US *** image dataset(POCUS)was used to validate our proposed COVID-LWNet framework *** classes of infectious COVID-19,bacterial pneumonia,and the healthy lung were investigated in this *** results showed that the performance of our proposed MnasNet classifier achieved the best accuracy score and shortest training time of 99.0%and 647.0 s,*** paper demonstrates the feasibility of using our proposed COVID-LWNet framework as a new mobilebased radiological tool for clinical diagnosis of COVID-19 and other lung diseases.

关键词： Coronavirus medical image processing artificial intelligence ultrasound

Efficacy of Gold Nanoparticles against Nephrotoxicity Induced by Schistosoma mansoni Infection in Mice

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Biomedical and Environmental Sciences 2016年第11期29卷 773-781页

作者： mohamed A Dkhil Mona F Khalil2 Amira A Bauom marwa SM Dia Saleh A1-Qura Department of Zoology College of ScienceKing Saud UniversityRiyadh 11451Saudi Arabia Department of Zoology and Entomology Faculty of ScienceHelwan UniversityCairo 11795Egypt Department of Laboratory Sciences College of Science&ArtsA1-RassQassim UniversityAL-Qaseam 51921Saudi Arabia Molecular Drug Evaluation Department National Organization for Drug Control&Research(NODCAR)Giza 12553Egypt

Objective In this study, the ameliorative effects of gold nanoparticles （gold NP） on the renal tissue damage in Schistosoma mansoni （S. mansoni）-infected mice was investigated. Methods High-resolution transmission electron microscopy was used for the characterization of NP. The gold NP at concentrations of 250, 500, and 1000 μg/kg body weight were inoculated into 5. mansoni-infected mice. Results The parasite caused alterations in the histological architecture. Furthermore, it induced a significant reduction in the renal glutathione levels; however, the levels of nitric oxide and malondialdehyde were significantly elevated. The parasite also managed to downregulate KIM-I, NGAL, MCP-1, and TGF-8 mRNA expression in infected animals. Notably, gold NP treatment in mice reduced the extent of histological impairment and renal oxidative damage. Gold NP were able to regulate gene expression impaired by 5. Mansoni infection. Conclusion The curative effect of gold NP against renal toxicity in 5. mansoni-infected mice is associated with their role as free radical scavengers.

关键词： Gold nanoparticles Schistosomiasis Renal damage Gene expression Histopathology Oxidative stress

Surgical outcomes of complicated cataract with pediatric trematode granulomatous uveitis

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International Journal of Ophthalmology(English edition) 2023年第3期16卷 354-360页

作者： Mahmoud M.Farouk Amr Mounir Mortada Ahmed Abozaid Engy mohamed Mostafa marwa Mahmoud Abdellah Department of Ophthalmology Sohag Faculty of MedicineSohag UniversitySohag 82524Egypt

AIM:To describe the clinical characteristics and surgical outcomes of complicated cataract with pediatric trematodal granulomatous uveitis(TGU).METHODS:Patients of cataract with TGU in the membranous(inactive) stage underwent cataract surgery with intraocular lens(IOL) *** history and ophthalmic examination were conducted for all cases,whereas Schimphlug imaging and corneal topography were done for some *** follow up was done on the 1st,2nd,and 5th postoperative days after ***,it was done at least at one,three,and six months *** and postoperative complications and the methods of their management were ***:Twelve eyes of 12 male children were included in this study ranging from 8 to *** mean best corrected Snellen visual acuity(BCVA) was significantly improved from 0.09±0.06 preoperatively to 0.37±0.11 at the final visit 6mo postoperatively(P<0.001).Schimphlug imaging and corneal topography showed flattening of the anterior surface of the inferior *** difficulties and complications included the poor dilatability of the drown down pupil,strong posterior synechia between the anterior lens capsule and the iris at the site of the inferior retrocorneal vascularized membrane and *** cases underwent primary hydrophobic IOL ***:Surgery for this type of cataract is relatively safe and *** is associated with some specific difficulties and complications that should be considered during surgery and follow up.

关键词： complicated cataract trematode granulomatous uveitis surgical outcomes

Telehealth utilization among Egyptian population and health institutional readiness:An exploratory study

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中西医结合护理杂志(英文) 2023年第3期5卷 188-196页

作者： Basma mohamed OSMAN Maaly Zayed mohamed Shaimaa Ali mohamed ISMAIL Lamiaa Saad Abd ALLAH marwa Mamdouh SHABAN Department of Community Health Nursing Faculty of NursingCairo UniversityCairoEgypt Department of Nursing Administration Faculty of NursingCairo UniversityCairoEgypt

Objective:This study aimed to assess the public’s perspectives and the health institutions’readiness for telehealth utilization in ***:A cross-sectional study design was employed,and data were collected from a convenient sample of 800 Egyptian citizens and 26 nursing administrators and information technology personnel from 16 governmental hospitals and 10 private hospitals between January and March *** Egyptian community utilization of telehealth questionnaire and the telemedicine hospital readiness assessment were used to collect the ***:The results revealed that 35.1%of the general Egyptian population used telehealth services and 43%expressed willingness to use them in *** perceived by the general Egyptian population,the most prevalent barriers to telehealth utilization were communication barriers(97.6%),lack of confidence in health professionals(77.6%),technological limitations(72.5%),the need for physical examination(25%),and privacy concerns(10%).Regarding hospital readiness,42%of governmental hospitals were not taking any initiative to implement telehealth services,and 15.4%were at the beginner level,meaning that some steps had been ***,the hospital was still far from being able to implement telehealth *** contrast,private hospitals were either at the beginner or advanced ***:Although the use of telehealth services in Egypt has increased,there is a need to address the barriers to public utilization and improve hospitals’readiness to implement telehealth services to enhance public usage.

关键词： Attitude barriers hospital readiness public use telehealth nursing practice nursing administration

Evaluation of On-Line MPPT Algorithms for PV-Based Battery Storage Systems

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Computers, Materials & Continua 2022年第11期73卷 3595-3611页

作者： Belqasem Aljafari Eydhah Almatrafi Sudhakar Babu Thanikanti Sara A.Ibrahim mohamed A.Enany marwa M.Ahmed Electrical Engineering Department College of EngineeringNajran UniversityNajran11001Saudi Arabia Mechanical Engineering Department College of Engineering-RabighKing Abdulaziz UniversityJeddahSaudi Arabia K.A.CARE Energy Research and Innovation Center King Abdulaziz UniversityJeddah21589Saudi Arabia Center of Excellence in Desalination Technology King Abdulaziz UniversityJeddahSaudi Arabia Department of Electrical and Electronics Engineering Chaitanya Bharathi Institute of TechnologyHyderabad500075India Electrical Power and Machines Department Faculty of EngineeringZagazig UniversityZagazig44519Egypt Electrical Engineering Department Faculty of EngineeringKing Abdul-Aziz UniversityJeddah80204Saudi Arabia

This paper presents a novel Simulink models with an evaluation study of more widely used On-Line Maximum Power Point tracking(MPPT)techniques for Photo-Voltaic based Battery Storage Systems(PV-BSS).To have a full comparative study in terms of the dynamic response,battery state of charge(SOC),and oscillations around the Maximum Power Point(MPP)of the PV-BSS to variations in climate conditions,these techniques are simulated in Matlab/*** introduced methodologies are classified into two types;the first type is conventional hill-climbing techniques which are based on instantaneous PV data measurements such as Perturb&Observe and Incremental Conductance *** second type is a novel proposed methodology is based on using solar irradiance and cell temperature measurements with pre-build Adaptive Neuro-Fuzzy Inference System(ANFIS)model to predict DC–DC converter optimum duty cycle to track *** evaluation study is introduced for conventional and proposed On-Line MPPT *** comparative study can be useful in specifying the appropriateness of the MPPT techniques for *** the introduced model can be used as a valued reference model for future research related to Soft Computing(SC)MPPT techniques.A significant improvement of SOC is achieved by the proposed model and methodology with high accuracy and lower oscillations.

关键词： Photo-voltaic based battery storage systems adaptive neuro-fuzzy inference system maximum power point tracking perturb&observe technique incremental conductance technique state of charge

Optimal Deep Learning Model Enabled Secure UAV Classification for Industry 4.0

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Computers, Materials & Continua 2023年第3期74卷 5349-5367页

作者： Khalid A.Alissa Mohammed Maray Areej A.Malibari Sana Alazwari Hamed Alqahtani mohamed K.Nour marwa Obbaya mohamed A.Shamseldin Mesfer Al Duhayyim SAUDI ARAMCO Cybersecurity Chair Networks and Communications DepartmentCollege of Computer Science and Information TechnologyImam Abdulrahman bin Faisal UniversityP.O.Box 1982Dammam31441Saudi Arabia Department of Information Systems College of Computer ScienceKing Khalid UniversityAbhaSaudi Arabia Department of Industrial and Systems Engineering College of EngineeringPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaif P.O.Box 11099Taif21944Saudi Arabia Department of Information Systems College of Computer ScienceCenter of Artificial IntelligenceUnit of CybersecurityKing Khalid UniversityAbhaSaudi Arabia Department of Computer Sciences College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Biomedical Engineering College of EngineeringPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Mechanical Engineering Faculty of Engineering and TechnologyFuture University in EgyptNew Cairo11835Egypt Department of Computer Science College of Sciences and Humanities-AflajPrince Sattam bin Abdulaziz UniversitySaudi Arabia

Emerging technologies such as edge computing,Internet of Things(IoT),5G networks,big data,Artificial Intelligence(AI),and Unmanned Aerial Vehicles(UAVs)empower,Industry 4.0,with a progressive production methodology that shows attention to the interaction between machine and human *** the literature,various authors have focused on resolving security problems in UAV communication to provide safety for vital *** current research article presents a Circle Search Optimization with Deep Learning Enabled Secure UAV Classification(CSODL-SUAVC)model for Industry 4.0 *** suggested CSODL-SUAVC methodology is aimed at accomplishing two core objectives such as secure communication via image steganography and image ***,the proposed CSODL-SUAVC method involves the following methods such as Multi-Level Discrete Wavelet Transformation(ML-DWT),CSO-related Optimal Pixel Selection(CSO-OPS),and signcryption-based *** proposed model deploys the CSO-OPS technique to select the optimal pixel points in cover *** secret images,encrypted by signcryption technique,are embedded into cover ***,the image classification process includes three components namely,Super-Resolution using Convolution Neural Network(SRCNN),Adam optimizer,and softmax *** integration of the CSO-OPS algorithm and Adam optimizer helps in achieving the maximum performance upon UAV *** proposed CSODLSUAVC model was experimentally validated using benchmark datasets and the outcomes were evaluated under distinct *** simulation outcomes established the supreme better performance of the CSODL-SUAVC model over recent approaches.

关键词： Unmanned Aerial Vehicles Artificial Intelligence emerging technologies Deep Learning Industry 4.0 image steganography

Novel CYP1B1 mutations and a possible prognostic use for surgical management of congenital glaucoma

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International Journal of Ophthalmology(English edition) 2019年第4期12卷 607-614页

作者： mohamed M.Khafagy Nadia El-Guendy marwa A Tantawy mohamed A.Eldaly Hala M.Elhilali Abdel Hady A.Abdel Wahab Ophthalmology Department Faculty of Medicine Cairo University Cancer Biology Department National Cancer Institute Cairo University Research Department Children's Cancer Hospital

AIM: To identify CYP1B1 gene mutations and evaluate their possible role as a prognostic factor for success rates in the surgical management of Egyptian congenital glaucoma ***: Totally 42 eyes of 29 primary congenital glaucoma patients were operated on with combined trabeculotomy/trabeculectomy with mitomycin-C and followed up at 1 d, 1 wk, 1, 6 and 12 mo postoperatively. Genomic DNA was extracted from peripheral blood leukocytes. Coding regions of CYP1B1 gene were amplified using 13 pairs of primers, screened for mutations using single-strand conformation polymorphism followed by sequencing of both strands. Efficacy of the operation was graded as either a success [maintaining intraocular pressure(IOP) less than 21 mm Hg with or without antiglaucoma medication], or a failure(IOP more than 21 mm Hg with topical antiglaucoma medications). RESULTS: Seven novel mutations out of a total of 15 different mutations were found in the CYP1B1 genes of 14 patients(48.2%). The presence of CYP1B1 gene mutations did not correlate with the failure of the surgery(P=0.156, odds ratio=3.611, 95%CI, 0.56 to 22.89); while the positive consanguinity strongly correlated with failure of the initial procedure(P=0.016, odds ratio=11.25, 95%CI, 1.57 to 80.30). However, the Kaplan-Meier survival analysis revealed a significantly lower time of IOP control in the subgroup with mutations in CYP1B1 versus the congenital primary glaucoma group without mutations(log rank test, P=0.015).CONCLUSION: Seven new CYP1B1 mutations are identified in Egyptian patients. Patients harboring confirmed mutations suffered from early failure of the initial surgery. CYP1B1 mutations could be considered as a prognostic factor for surgery in primary congenital glaucoma.

关键词： CYP1B1 mutations primary congenital glaucoma intraocular pressure trabeculotomy/trabeculectomy with mitomycin-C.

Metaheuristic with Deep Learning Enabled Biomedical Bone Age Assessment and Classification Model

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Computers, Materials & Continua 2022年第12期73卷 5473-5489页

作者： Mesfer Al Duhayyim Areej A.Malibari marwa Obayya mohamed K.Nour Ahmed S.Salama mohamed I.Eldesouki Abu Sarwar Zamani Mohammed Rizwanullah Department of Computer Science College of Sciences and Humanities-AflajPrince Sattam bin Abdulaziz UniversitySaudi Arabia Department of Industrial and Systems Engineering College of EngineeringPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Biomedical Engineering College of EngineeringPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Electrical Engineering Faculty of Engineering&TechnologyFuture University in EgyptNew Cairo11845Egypt Department of Information System College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

The skeletal bone age assessment(BAA)was extremely implemented in development prediction and auxiliary analysis of medicinal issues.X-ray images of hands were detected from the estimation of bone age,whereas the ossification centers of epiphysis and carpal bones are important *** typical skeletal BAA approaches remove these regions for predicting the bone age,however,few of them attain suitable efficacy or *** BAA techniques with deep learning(DL)methods are reached the leading efficiency on manual and typical ***,this study introduces an intellectual skeletal bone age assessment and classification with the use of metaheuristic with deep learning(ISBAAC-MDL)*** presented ISBAAC-MDL technique majorly focuses on the identification of bone age prediction and classification *** attain this,the presented ISBAAC-MDL model derives a mask Region-related Convolutional Neural Network(Mask-RCNN)with MobileNet as baseline model to extract *** by,the whale optimization algorithm(WOA)is implemented for hyperparameter tuning of the MobileNet *** last,Deep Feed-Forward Module(DFFM)based age prediction and Radial Basis Function Neural Network(RBFNN)based stage classification approach is *** experimental evaluation of the ISBAAC-MDL model is tested using benchmark dataset and the outcomes are assessed over distinct *** experimental outcomes reported the better performances of the ISBAACMDL model over recent approaches with maximum accuracy of 0.9920.

关键词： Biomedical images bone age assessment age prediction computer vision deep learning image classification

Gaussian Optimized Deep Learning-based Belief Classification Model for Breast Cancer Detection

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Computers, Materials & Continua 2022年第11期73卷 4123-4138页

作者： Areej A.Malibari marwa Obayya mohamed K.Nour Amal S.Mehanna Manar Ahmed Hamza Abu Sarwar Zamani Ishfaq Yaseen Abdelwahed Motwakel Department of Industrial and Systems Engineering College of EngineeringPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh 11671Saudi Arabia Department of Biomedical Engineering College of EngineeringPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Digital Media Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11845Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam Bin Abdulaziz UniversityAlKharjSaudi Arabia

With the rapid increase of new cases with an increased mortality rate,cancer is considered the second and most deadly disease *** cancer is the most widely affected cancer worldwide,with an increased death rate *** to radiologists’processing of mammogram images,many computer-aided diagnoses have been developed to detect breast *** detection of breast cancer will reduce the death rate *** early diagnosis of breast cancer using the developed computer-aided diagnosis(CAD)systems still needed to be enhanced by incorporating innovative deep learning technologies to improve the accuracy and sensitivity of the detection system with a reduced false positive *** paper proposed an efficient and optimized deep learning-based feature selection approach with this *** model selects the relevant features from the mammogram images that can improve the accuracy of malignant detection and reduce the false alarm *** learning is used in the extraction of features *** ext,a convolution neural network,is used to extract the *** two feature vectors are fused and optimized with enhanced Butterfly Optimization with Gaussian function(TL-CNN-EBOG)to select the final most relevant *** optimized features are applied to the classifier called Deep belief network(DBN)to classify the benign and malignant *** feature extraction and classification process used two datasets,breast,and *** to the existing methods,the optimized deep learning-based model secured 98.6%of improved accuracy on the breast dataset and 98.85%of improved accuracy on the MIAS dataset.

关键词： Breast cancer detection computer-aided diagnosis(CAD) deep learning CNN entropy butterfly optimization