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Childhood asthma biomarkers including zinc: An exploratory crosssectional study

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World Journal of Clinical Pediatrics 2024年第1期13卷 31-40页

作者： Hoda Atef Abdelsattar Ibrahim mona Mohsen Boles Salep Aziz Hanna Dina Mahmoud Khaled Mohamed abdelhamid El-Khashab Pediatric Clinical Nutrition Unit Faculty of MedicineCairo UniversityCairo 12613Egypt Department of Pediatrics Faculty of MedicineCairo UniversityCairo 12613Egypt Department of Clinical Pathology Faculty of MedicineCairo UniversityCairo 12613Egypt

BACKGROUND Childhood bronchial asthma(BA)is a chronic inflammatory respiratory *** conditions,including zinc deficiency,can affect such allergic *** To outline the difference in serum zinc levels between asthmatic children and healthy *** A cross-sectional study was carried out at Children’s Hospital,Cairo University,investigating serum zinc levels in children with BA(n=40)and healthy children(n=21).Other markers included serum ferritin,iron,hemoglobin(Hb),and immunoglobulin E(IgE)*** t-tests and Mann-Whinny tests were used for *** Kruskal-Wallis test was applied to compare serum ferritin and IgE levels with regard to asthma ***'s rank correlation was performed to explore the relationship between serum ferritin levels and both iron and Hb levels in asthmatic *** Children with BA had higher levels of zinc,yet the difference was not significant(P=0.115).Serum ferritin and IgE levels were significantly higher in asthmatic children(P=0.006 and 0.001,respectively),yet their levels did not differ significantly by severity(P=0.623 and 0.126,respectively).There was a nonsignificant weak correlation between serum ferritin levels and both serum iron and Hb *** Serum zinc levels do not seem to differ between asthmatic children and healthy *** ferritin levels may be a marker of asthma *** IgE levels are not markers of asthma severity.

关键词： Children Asthma Zinc Ferritin

Facial Expression Recognition Model Depending on Optimized Support Vector Machine

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Computers, Materials & Continua 2023年第7期76卷 499-515页

作者： Amel Ali Alhussan Fatma M.Talaat El-Sayed M.El-kenawy Abdelaziz A.abdelhamid Abdelhameed Ibrahim Doaa Sami Khafaga mona Alnaggar Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Machine Learning&Information Retrieval Department Faculty of Artificial IntelligenceKafrelsheikh UniversityKafrelsheikh33516Egypt Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Robotics and Intelligent Machines Department Faculty of Artificial IntelligenceKafrelsheikh UniversityKafrelsheikh33516Egypt

In computer vision,emotion recognition using facial expression images is considered an important research *** learning advances in recent years have aided in attaining improved results in this *** to recent studies,multiple facial expressions may be included in facial photographs representing a particular type of *** is feasible and useful to convert face photos into collections of visual words and carry out global expression *** main contribution of this paper is to propose a facial expression recognitionmodel(FERM)depending on an optimized Support Vector Machine(SVM).To test the performance of the proposed model(FERM),AffectNet is *** uses 1250 emotion-related keywords in six different languages to search three major search engines and get over 1,000,000 facial photos *** FERM is composed of three main phases:(i)the Data preparation phase,(ii)Applying grid search for optimization,and(iii)the categorization *** discriminant analysis(LDA)is used to categorize the data into eight labels(neutral,happy,sad,surprised,fear,disgust,angry,and contempt).Due to using LDA,the performance of categorization via SVM has been obviously *** search is used to find the optimal values for hyperparameters of SVM(C and gamma).The proposed optimized SVM algorithm has achieved an accuracy of 99%and a 98%F1 score.

关键词： Facial expression recognition machine learning linear dis-criminant analysis(LDA) support vector machine(SVM) grid search

Al-Biruni Earth Radius(BER)Metaheuristic Search Optimization Algorithm

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Computer Systems Science & Engineering 2023年第5期45卷 1917-1934页

作者： El-Sayed M.El-kenawy Abdelaziz A.abdelhamid Abdelhameed Ibrahim Seyedali Mirjalili Nima Khodadad mona A.Al duailij Amel Ali Alhussan Doaa Sami Khafaga Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Centre for Artificial Intelligence Research and Optimization Torrens University AustraliaFortitude ValleyQLD 4006Australia Yonsei Frontier Lab Yonsei UniversitySeoul03722Korea Department of Civil and Environmental Engineering Florida International UniversityMiamiUSA Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia

Metaheuristic optimization algorithms present an effective method for solving several optimization problems from various types of applications and *** metaheuristics and evolutionary optimization algorithms have been emerged recently in the literature and gained widespread attention,such as particle swarm optimization(PSO),whale optimization algorithm(WOA),grey wolf optimization algorithm(GWO),genetic algorithm(GA),and gravitational search algorithm(GSA).According to the literature,no one metaheuristic optimization algorithm can handle all present optimization *** novel optimization methodologies are still *** Al-Biruni earth radius(BER)search optimization algorithm is proposed in this *** proposed algorithm was motivated by the behavior of swarm members in achieving their global *** search space around local solutions to be explored is determined by Al-Biruni earth radius calculation method.A comparative analysis with existing state-of-the-art optimization algorithms corroborated the findings of BER’s validation and testing against seven mathematical optimization *** results show that BER can both explore and avoid local *** has also been tested on an engineering design optimization *** results reveal that,in terms of performance and capability,BER outperforms the performance of state-of-the-art metaheuristic optimization algorithms.

关键词： Metaheuristics evolutionary optimization exploration exploitation mutation Al-biruni earth radius

Adaptive Dynamic Dipper Throated Optimization for Feature Selection in Medical Data

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Computers, Materials & Continua 2023年第4期75卷 1883-1900页

作者： Ghada Atteia El-Sayed M.El-kenawy Nagwan Abdel Samee mona M.Jamjoom Abdelhameed Ibrahim Abdelaziz A.abdelhamid Ahmad Taher Azar Nima Khodadadi Reham A.Ghanem Mahmoud Y.Shams Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Faculty of Computers and Artificial Intelligence Benha UniversityBenha13518Egypt College of Computer and Information Sciences Prince Sultan UniversityRiyadh11586Saudi Arabia Department of Civil Engineering University of Science and TechnologyMiami33101USA Department of Civil and Environmental Engineering Florida International UniversityMiamiUSA Oral Biology Department Faculty of Oral and Dental MedicineDelta University for Science and TechnologyGamasaEgypt Faculty of Artificial Intelligence Kafrelsheikh UniversityKafrelsheikh33511Egypt

The rapid population growth results in a crucial problem in the early detection of diseases inmedical *** all the cancers unveiled,breast cancer is considered the second most severe ***,an exponential rising in death cases incurred by breast cancer is expected due to the rapid population growth and the lack of resources required for performing medical *** recent advances in machine learning could help medical staff in diagnosing diseases as they offer effective,reliable,and rapid responses,which could help in decreasing the death *** this paper,we propose a new algorithm for feature selection based on a hybrid between powerful and recently emerged optimizers,namely,guided whale and dipper throated *** proposed algorithm is evaluated using four publicly available breast cancer *** evaluation results show the effectiveness of the proposed approach from the accuracy and speed *** prove the superiority of the proposed algorithm,a set of competing feature selection algorithms were incorporated into the conducted *** addition,a group of statistical analysis experiments was conducted to emphasize the superiority and stability of the proposed *** best-achieved breast cancer prediction average accuracy based on the proposed algorithm is 99.453%.This result is achieved in an average time of 3.6725 s,the best result among all the competing approaches utilized in the experiments.

关键词： Medical dataset breast cancer guided whale optimizer dipper throated optimizer feature selection meta-heuristics

Metaheuristic Optimization Through Deep Learning Classification of COVID-19 in Chest X-Ray Images

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Computers, Materials & Continua 2022年第11期73卷 4193-4210页

作者： Nagwan Abdel Samee El-Sayed M.El-Kenawy Ghada Atteia mona M.Jamjoom Abdelhameed Ibrahim Abdelaziz A.abdelhamid Noha E.El-Attar Tarek Gaber Adam Slowik Mahmoud Y.Shams Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh 11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura 35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura 35712Egypt Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh 11671Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura University35516MansouraEgypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams University11566CairoEgypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Faculty of Computers and Artificial Intelligence Benha UniversityEgypt School of Science Engineeringand EnvironmentUniversity of SalfordUK Faculty of Computers and Informatics Suez Canal UniversityIsmailia41522Egypt Koszalin University of Technology Poland Faculty of Artificial Intelligence Kafrelsheikh UniversityKafrelsheikh33511Egypt

As corona virus disease(COVID-19)is still an ongoing global outbreak,countries around the world continue to take precautions and measures to control the spread of the *** of the excessive number of infected patients and the resulting deficiency of testing kits in hospitals,a rapid,reliable,and automatic detection of COVID-19 is in extreme need to curb the number of *** analyzing the COVID-19 chest X-ray images,a novel metaheuristic approach is proposed based on hybrid dipper throated and particle swarm *** lung region was segmented from the original chest X-ray images and augmented using various transformation ***,the augmented images were fed into the VGG19 deep network for feature *** the other hand,a feature selection method is proposed to select the most significant features that can boost the classification ***,the selected features were input into an optimized neural network for *** neural network is optimized using the proposed hybrid *** experimental results showed that the proposed method achieved 99.88%accuracy,outperforming the existing COVID-19 detection *** addition,a deep statistical analysis is performed to study the performance and stability of the proposed *** results confirm the effectiveness and superiority of the proposed approach.

关键词： Covid-19 feature selection dipper throated optimization particle swarm optimization deep learning

Effect of Head Position on the Success Rate of Blind Intubation through Air Q Laryngeal Mask in Morbidly Obese Patients

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Open Journal of Anesthesiology 2017年第8期7卷 240-252页

作者： mona Hossam Eldin abdelhamid Sahar Sayed Ismail Badawy Norhan Abdel Alim Ali Ramy Melad Ramzy Aziz Department of Anesthesia Critical Care and Pain Management Faculty of Medicine Cairo University Cairo Egypt

Aim: To evaluate the effect of head positioning whether neutral or sniffing position on the conduct of intubation through air Q in morbidly obese patients. Patients and method: This study was conducted on 90 patients with body mass index equal or above 40 who were scheduled for surgery under GA and were randomly divided into 2 equal groups: Group N (Gn) in which blind intubation through air Q was done in neutral position. Group S (Gs) in which blind intubation was done in sniffing position. Proper airway assessment of the patients was done. Basic monitoring was attached;Induction of anaesthesia was achieved by Fentanyl 2 ug/kg, Propofol 1.5 - 2.5 mg/kg and Atracurium 0.5 mg/kg. Maintenance of anaesthesia was achieved by Sevoflurane, Atracurium, oxygen and air. When neuromuscular blockade was complete, the head of the patient was adjusted according to their group. The supraglottic device was inserted and connected to capnography, thereafter a well lubricated proper sized ETT was passed through the air Q. We recorded a baseline reading of HR, SBP, DBP, MBP, and oxygen saturation. A second reading was taken after induction of anesthesia, just before intubation. The third reading was recorded after intubation while further readings were measured 1, 3, 5, 10, 15 min after intubation. After ETT removal, we observed the patients in the recovery room at 0, 3 & 24 hours for possible postoperative complications. Results: There was no statistical difference between the two groups regarding the demographic data. Although the intubation in sniffing position has a higher success rate from the first time than the neutral position, the results were statistically insignificant, regarding the mean duration of blind intubation trials through the Air Q and postoperative complications. Conclusion: Although the sniffing position improves glottic visualization, the change of head position had no effect on the success rate of blind intubation through air Q in obese patients.

关键词： Air Q Head Position Obese Patient Intubation