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

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 

作者机构：Department of Information TechnologyCollege of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh 11671Saudi Arabia Department of Communications and ElectronicsDelta Higher Institute of Engineering and TechnologyMansoura 35111Egypt Faculty of Artificial IntelligenceDelta University for Science and TechnologyMansoura 35712Egypt Department of Computer SciencesCollege of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh 11671Saudi Arabia Computer Engineering and Control Systems DepartmentFaculty of EngineeringMansoura University35516MansouraEgypt Department of Computer ScienceFaculty of Computer and Information SciencesAin Shams University11566CairoEgypt Department of Computer ScienceCollege of Computing and Information TechnologyShaqra University11961Saudi Arabia Faculty of Computers and Artificial IntelligenceBenha UniversityEgypt School of ScienceEngineeringand EnvironmentUniversity of SalfordUK Faculty of Computers and InformaticsSuez Canal UniversityIsmailia41522Egypt Koszalin University of TechnologyPoland Faculty of Artificial IntelligenceKafrelsheikh UniversityKafrelsheikh33511Egypt 

出 版 物：《Computers, Materials & Continua》 (计算机、材料和连续体（英文）)

年 卷 期：2022年第73卷第11期

页      面：4193-4210页

核心收录：

学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：Princess Nourah bint Abdulrahman University Researchers Supporting Project Number(PNURSP2022R104) Princess Nourah bint Abdulrahman University Riyadh Saudi Arabia 

主　　题：Covid-19 feature selection dipper throated optimization particle swarm optimization deep learning 

摘      要：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.