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Artificial Intelligence Based Meteorological Parameter Forecasting for Optimizing Response of Nuclear Emergency Decision Support System

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原子能科学技术 2024年第10期58卷 2068-2076页

作者： BILAL Ahmed Khan HASEEB ur rehman QAISAR Nadeem muhammad Ahmad Naveed Qureshi JAWARIA Ahad muhammad Naveed Akhtar AMJAD Farooq MASROOR Ahmad Pakistan Institute of Engineering and Applied Sciences Islamabad 44000Pakistan

This paper presents a novel artificial intelligence (AI) based approach to predict crucial meteorological parameters such as temperature,pressure,and wind speed,typically calculated from computationally intensive weather research and forecasting (WRF) *** meteorological data is indispensable for simulating the release of radioactive effluents,especially in dispersion modeling for nuclear emergency decision support *** of meteorological conditions during nuclear emergencies using the conventional WRF model is very complex and ***,a new artificial neural network (ANN) based technique was proposed as a viable alternative for meteorological prediction.A multi-input multi-output neural network was trained using historical site-specific meteorological data to forecast the meteorological *** evaluation of this technique was conducted to test its performance in forecasting various parameters including atmospheric pressure,temperature,and wind speed components in both East-West and North-South *** performance of developed network was evaluated on an unknown dataset,and acquired results are within the acceptable range for all meteorological *** show that ANNs possess the capability to forecast meteorological parameters,such as temperature and pressure,at multiple spatial locations within a grid with high accuracy,utilizing input data from a single ***,accuracy is slightly compromised when predicting wind speed *** mean square error (RMSE) was utilized to report the accuracy of predicted results,with values of 1.453℃for temperature,77 Pa for predicted pressure,1.058 m/s for the wind speed of U-component and 0.959 m/s for the wind speed of *** conclusion,this approach offers a precise,efficient,and wellinformed method for administrative decision-making during nuclear emergencies.

关键词： prediction of meteorological parameters weather research and forecasting model artificial neural networks nuclear emergency support system

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Effect of Light Emitting Diodes (LEDs) on Growth, Mineral Composition, and Nutritional Value of Wheat & Lentil Sprouts

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Phyton-International Journal of Experimental Botany 2024年第6期93卷 1117-1128页

作者： Abdul Momin Amana Khatoon Wajahat Khan Dilsat Bozdoğan Konuşkan muhammad Mudasar Aslam muhammad Jamil Shafiq ur rehman Baber Ali Alevcan Kaplan Sana Wahab muhammad Nauman Khan Sezai Ercisli Mohammad Khalid Al-Sadoon Department of Botany Kohat University of Science&TechnologyKohat26000Pakistan Department of Food Engineering Faculty of AgricultureHatay Mustafa Kemal UniversityHatay31000Türkiye Department of Botany University of Science&TechnologyBannu28100Pakistan Department of Biotechnology and Genetic Engineering Kohat University of Science&TechnologyKohat26000Pakistan Department of Biology University of HaripurKhyber Pakhtunkhwa22620Pakistan School of Science Western Sydney UniversityPenrithNew South Wales2151Australia Department of Crop and Animal Production Sason Vocational SchoolBatman UniversityBatman72060Türkiye Department of Plant Sciences Quaid-i-Azam UniversityIslamabad45320Pakistan Department of Botany Islamia College PeshawarPeshawar25120Pakistan Department of Horticulture Agricultural FacultyAtaturk UniversityErzurum25240Türkiye HGF Agro Ata TeknokentErzurumTR-25240Türkiye Department of Zoology College of ScienceKing Saud UniversityRiyadh11451Saudi Arabia

Sprouts are ready-to-eat and are recognized worldwide as functional components of the human *** advances in innovative agricultural techniques could enable an increase in the production of healthy *** use of light-emitting diode(LED)in indoor agricultural production could alter the biological feedback loop,increasing the functional beneﬁts of plant foods such as wheat and lentil sprouts and promoting the bioavailability of *** effects of white(W),red(R),and blue(B)light were investigated on the growth parameters and nutritional value of wheat and lentil *** the laboratory,seeds were sown under three different LED treat-ments:white,red,and blue light,while normal incandescent light served as a *** seed germina-tion improved by 18.34%and 12.67%for wheat and 18.34%and 12.67%for lentil sprouts under LED treatments R and B,*** increase in total soluble protein and sugar by 33.4%and 9.23%in wheat and by 31.5%and 5.87%in lentils was observed under the R LED *** C concentrations in wheat and lentils were signiﬁcantly increased by R LED compared to all other *** parameters,including potassium and sodium concentrations,were signiﬁcantly increased under red and blue light compared to the control;white light,on the other hand,signiﬁcantly decreased all these *** to the experimental data,red and blue LED light could be beneﬁcial in the production of functional wheat and lentil sprouts with high nutrient concentrations.

关键词： Growth parameters LED nutritional value sprouts total soluble proteins

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Simultaneously enhancing coercivity and remanence of hot-deformed Nd-Fe-B magnets by flake copper powder assisted DyF_(3) interflake addition

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Journal of Rare Earths 2024年第7期42卷 1282-1288,I0003页

作者： Yikuan Hu Jiajie Li Shengyu Sun Shuwei Zhong Munan Yang Xiaoqiang Yu Sajjad ur rehman Xi Yu Jiangxi Key Laboratory for Rare Earth Magnetic Materials and Devices College of Rare EarthsJiangxi University of Science and TechnologyGanzhou341000 National Rare Earth Functional Materials Innovation Center Ganzhou341000China Ganzhou Fortune Electronic Ltd. Ganzhou341000China

It is still a challenge to simultaneously enhance coercivity(H_(cj))and remanence(J_(r))of hot-deformed Nd-Fe-B magnet due to the coercivity-remanence trade-off ***,we achieved this balance between H_(cj)and Jr by flake Cu powder assisted DyF_(3)interflake *** Hcj increases from 1218 to 1496 kA/m and Jr increases from 1.32 to 1.34 T compared with the original *** show that the width of coarse grain layers reduces because of the introduction of flake Cu,which increases the contact areas of the adjacent grains at ribbon interfaces and suppresses the excessive growth of *** stronger degree of texture and higher density compared with the original magnet should take the responsibility for the increase of J_(r).Additionally,the aggregation regions of rare earth rich(RE-rich)phase reduce and the betterment of the microstructure is another reason for the enhancement of Jr in the flake Cu aided DyF_(3)hot-deformed *** strategy of using flake powder additives provides a promising method for optimizing microstructure and enhancing magnetic properties of hot-deformed Nd-Fe-B magnets.

关键词： Rare earths Nd-Fe-B Hot-deformed magnet Flake powder Interflake addition Remanence

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Empowering Diagnosis: Cutting-Edge Segmentation and Classification in Lung Cancer Analysis

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Computers, Materials & Continua 2024年第6期79卷 4963-4977页

作者： Iftikhar Naseer Tehreem Masood Sheeraz Akram Zulfiqar Ali Awais Ahmad Shafiq ur rehman Arfan Jaffar Faculty of Computer Sciences&Information Technology The Superior UniversityLahore54000Pakistan Intelligent Data Visual Computing Research(IDVCR) Lahore54000Pakistan Information System Department College of Computer and Information SciencesImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11432Saudi Arabia School of Computer Science and Electronic Engineering(CSEE) University of EssexWivenhoe ParkColchesterCO43SQUK

Lung cancer is a leading cause of global mortality *** detection of pulmonary tumors can significantly enhance the survival rate of ***,various Computer-Aided Diagnostic(CAD)methods have been developed to enhance the detection of pulmonary nodules with high ***,the existing method-ologies cannot obtain a high level of specificity and *** present study introduces a novel model for Lung Cancer Segmentation and Classification(LCSC),which incorporates two improved architectures,namely the improved U-Net architecture and the improved AlexNet *** LCSC model comprises two distinct *** first stage involves the utilization of an improved U-Net architecture to segment candidate nodules extracted from the lung ***,an improved AlexNet architecture is employed to classify lung *** the first stage,the proposed model demonstrates a dice accuracy of 0.855,a precision of 0.933,and a recall of 0.789 for the segmentation of candidate *** suggested improved AlexNet architecture attains 97.06%accuracy,a true positive rate of 96.36%,a true negative rate of 97.77%,a positive predictive value of 97.74%,and a negative predictive value of 96.41%for classifying pulmonary cancer as either benign or *** proposed LCSC model is tested and evaluated employing the publically available dataset furnished by the Lung Image Database Consortium and Image Database Resource Initiative(LIDC-IDRI).This proposed technique exhibits remarkable performance compared to the existing methods by using various evaluation parameters.

关键词： Lung cancer segmentation AlexNet U-Net classification

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Image Fusion Using Wavelet Transformation and XGboost Algorithm

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Computers, Materials & Continua 2024年第4期79卷 801-817页

作者： Shahid Naseem tariq Mahmood Amjad rehman Khan Umer Farooq Samra Nawazish Faten S.Alamri Tanzila Saba Department of Information Sciences Division of S&TUniversity of EducationLahore54770Pakistan Artificial Intelligence and Data Analytics(AIDA)Lab CCIS Prince Sultan UniversityRiyadh11586Saudi Arabia Faculty of Information Sciences University of EducationVehari CampusVehari61100Pakistan Department of Computer Science University of Engineering and TechnologyTaxila47050Pakistan Department of Mathematical Sciences College of SciencePrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia

Recently,there have been several uses for digital image *** fusion has become a prominent application in the domain of imaging *** create one final image that provesmore informative and helpful compared to the original input images,image fusion merges two or more initial images of the same *** fusion aims to produce,enhance,and transform significant elements of the source images into combined images for the sake of human visual *** fusion is commonly employed for feature extraction in smart robots,clinical imaging,audiovisual camera integration,manufacturing process monitoring,electronic circuit design,advanced device diagnostics,and intelligent assembly line robots,with image quality varying depending on *** research paper presents various methods for merging images in spatial and frequency domains,including a blend of stable and curvelet transformations,everageMax-Min,weighted principal component analysis(PCA),HIS(Hue,Intensity,Saturation),wavelet transform,discrete cosine transform(DCT),dual-tree Complex Wavelet Transform(CWT),and multiple wavelet *** fusion methods integrate data from several source images of an identical target,thereby enhancing information in an extremely efficient *** precisely,in imaging techniques,the depth of field constraint precludes images from focusing on every object,leading to the exclusion of certain *** tackle thess challanges,a very efficient multi-focus wavelet decomposition and recompositionmethod is *** use of these wavelet decomposition and recomposition techniques enables this method to make use of existing optimized wavelet code and filter *** simulated outcomes provide evidence that the suggested approach initially extracts particular characteristics from images in order to accurately reflect the level of clarity portrayed in the original *** study enhances the performance of the eXtreme Gradient Boosting(XGBoos

关键词： Image fusion max-min average CWT XGBoost DCT inclusive innovations spatial and frequency domain

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Outsmarting Android Malware with Cutting-Edge Feature Engineering and Machine Learning Techniques

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Computers, Materials & Continua 2024年第4期79卷 651-673页

作者： Ahsan Wajahat Jingsha He Nafei Zhu tariq Mahmood Tanzila Saba Amjad rehman Khan Faten S.A.lamri Faculty of Information Technology Beijing University of TechnologyBeijing100124China Artificial Intelligence and Data Analytics(AIDA)Lab CCIS Prince Sultan UniversityRiyadh11586Saudi Arabia Faculty of Information Sciences University of EducationVehari CampusVehari61100Pakistan Department of Mathematical Sciences College of SciencePrincess Nourah bint Abdulrahman UniversityRiyadh84428Saudi Arabia

The growing usage of Android smartphones has led to a significant rise in incidents of Android malware andprivacy *** escalating security concern necessitates the development of advanced technologies capableof automatically detecting andmitigatingmalicious activities in Android applications(apps).Such technologies arecrucial for safeguarding user data and maintaining the integrity of mobile devices in an increasingly digital *** methods employed to detect sensitive data leaks in Android apps are hampered by two major limitationsthey require substantial computational resources and are prone to a high frequency of false *** meansthat while attempting to identify security breaches,these methods often consume considerable processing powerand mistakenly flag benign activities as malicious,leading to inefficiencies and reduced reliability in *** proposed approach includes a data preprocessing step that removes duplicate samples,managesunbalanced datasets,corrects inconsistencies,and imputes missing values to ensure data *** Minimaxmethod is then used to normalize numerical data,followed by feature vector extraction using the Gain ratio andChi-squared test to identify and extract the most significant characteristics using an appropriate prediction *** study focuses on extracting a subset of attributes best suited for the task and recommending a predictivemodel based on domain expert *** proposed method is evaluated using Drebin and TUANDROMDdatasets containing 15,036 and 4,464 benign and malicious samples,*** empirical result shows thatthe RandomForest(RF)and Support VectorMachine(SVC)classifiers achieved impressive accuracy rates of 98.9%and 98.8%,respectively,in detecting unknown Androidmalware.A sensitivity analysis experiment was also carriedout on all three ML-based classifiers based on MAE,MSE,R2,and sensitivity parameters,resulting in a flawlessperformance for both *** app

关键词： Android malware detection machine learning SVC K-Nearest Neighbors(KNN) RF

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Self-supported copper-based gas diffusion electrodes improve the local CO_(2)concentration for efficient electrochemical CO_(2)reduction

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Frontiers of Chemical Science and Engineering 2024年第3期18卷 51-62页

作者： Azeem Mustafa Bachirou Guene Lougou Yong Shuai Zhijiang Wang Haseeb-ur-rehman Samia Razzaq Wei Wang Ruming Pan Jiupeng Zhao Key Laboratory of Aerospace Thermophysics of MIIT Harbin Institute of TechnologyHarbin150001China School of Energy Science and Engineering Harbin Institute of TechnologyHarbin150001China MIIT Key Laboratory of Critical Materials Technology for New Energy Conversion and Storage School of Chemistry and Chemical EngineeringHarbin Institute of TechnologyHarbin150001China Mechanical Engineering Department University of Engineering and TechnologyTaxila47050Pakistan School of Aerospace Mechanical and Mechatronics EngineeringUniversity of SydneySydney2006Australia

Electrochemical CO_(2)reduction is a sustainable approach in green chemistry that enables the production of valuable chemicals and fuels while mitigating the environmental impact associated with CO_(2)*** its several advantages,this technology suffers from an intrinsically low CO_(2)solubility in aqueous solutions,resulting in a lower local CO_(2)concentration near the electrode,which yields lower current densities and restricts product *** diffusion electrodes(GDEs),particularly those with tubular architectures,can solve these issues by increasing the local CO_(2)concentration and triple-phase interface,providing abundant electroactive sites to achieve superior reaction *** this study,robust and self-supported Cu flow-through gas diffusion electrodes(FTGDEs)were synthesized for efficient formate production via electrochemical CO_(2)*** were further compared with traditional Cu electrodes,and it was found that higher local CO_(2)concentration due to improved mass transfer,the abundant surface area available for the generation of the triple-phase interface,and the porous structure of Cu FTGDEs enabled high formate Faradaic efficiency(76%)and current density(265 mA¸cm^(−2))at–0.9 V *** hydrogen electrode(RHE)in 0.5 mol·L^(−1)*** combined phase inversion and calcination process of the Cu FTGDEs helped maintain a stable operation for several *** catalytic performance of the Cu FTGDEs was further investigated in a non-gas diffusion configuration to demonstrate the impact of local gas concentration on the activity and performance of electrochemical CO_(2)*** study demonstrates the potential of flow-through gas-diffusion electrodes to enhance reaction kinetics for the highly efficient and selective reduction of CO_(2),offering promising applications in sustainable electrochemical processes.

关键词： CO_(2)electroreduction flow-through delivery hollow fiber structure local concentration formate

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Rice-wheat comparative genomics:Gains and gaps

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The Crop Journal 2024年第3期12卷 656-669页

作者： Akila Wijerathna-Yapa Ruchi Bishnoi Buddhini Ranawaka Manu Maya Magar Hafeez ur rehman Swati G.Bharad Michal T.Lorenc Vinita Ramtekey Sasha Gohar Charu Lata Md.Harun-Or-Rashid Maryam Razzaq muhammad Sajjad Bhoja *** School of Agriculture and Food Sustainability The University of QueenslandSt LuciaQLD 4072Australia ARC Centre of Excellence for Plant Success in Nature and Agriculture The University of QueenslandSt LuciaQLD 4072Australia Department of Genetics and Plant Breeding College of AgricultureUmmedganj-KotaAgriculture UniversityKotaRajasthan 324001India Centre for Agriculture and the Bioeconomy Queensland University of Technology(QUT)2 George StreetBrisbaneQLD 4000Australia UWA School of Agriculture and Environment The University of Western Australia35 Stirling HighwayCrawleyWA 6009Australia Nepal Agriculture Research Council KhumaltarLalitpurNepal Department of Agronomy University of AgricultureFaisalabad 38040Pakistan Department of Agricultural Botany Dr Panjabrao Deshmukh Krishi VidyapeethAkola 444104MaharashtraIndia ICAR-Indian Institute of Seed Science MauUttar Pradesh 275103India School of Natural Sciences Macquarie UniversityMacquarie ParkNSW 2109Australia ICAR-Indian Institute of Wheat and Barley Research Flowrdale 54642ShimlaIndia International Maize and Wheat Improvement Center(CIMMYT)Bangladesh Office Gulshan-2Dhaka 1212Bangladesh Center for Seed Science University of AgricultureFaisalabad 38000Pakistan Department of Biosciences COMSATS University IslamabadPark RoadTarlai KalanIslamabad 45550Pakistan CGIAR’s Excellence in Breeding(EiB)Platform/Accelerated Breeding Initiative International Maize and Wheat Improvement Center(CIMMYT)El Batán 56237Mexico

Rice and wheat provide nearly 40%of human calorie and protein *** share a common ancestor and belong to the Poaceae(grass)*** their genetic homology is crucial for developing new cultivars with enhanced *** wheat genes and gene families have been characterized based on their rice ***–wheat orthology can identify genetic regions that regulate similar traits in both ***–wheat comparative genomics can identify candidate wheat genes in a genomic region identified by association or QTL mapping,deduce their putative functions and biochemical pathways,and develop molecular markers for marker-assisted breeding.A knowledge of gene homology facilitates the transfer between crops of genes or genomic regions associated with desirable traits by genetic engineering,gene editing,or wide crossing.

关键词： Comparative genomics Orthologs Genes Synteny Genetic engineering Molecular breeding

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Improving Thyroid Disorder Diagnosis via Ensemble Stacking and Bidirectional Feature Selection

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Computers, Materials & Continua 2024年第3期78卷 4225-4241页

作者： muhammad Armghan Latif Zohaib Mushtaq Saad Arif Sara rehman muhammad Farrukh Qureshi Nagwan Abdel Samee Maali Alabdulhafith Yeong Hyeon Gu Mohammed A.Al-masni Department of Computer and Information System Cleveland State UniversityOhio44115USA Department of Electrical Electronics and Computer SystemsCollege of Engineering and TechnologyUniversity of SargodhaSargodha40100Pakistan Department of Mechanical Engineering College of EngineeringKing Faisal UniversityAl-Ahsa31982Saudi Arabia Department of Biomedical Engineering Riphah International UniversityIslamabad44000Pakistan Department of Electrical Engineering Riphah International UniversityIslamabad44000Pakistan Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Artificial Intelligence College of Software and Convergence TechnologySejong UniversitySeoul05006Korea

Thyroid disorders represent a significant global health challenge with hypothyroidism and hyperthyroidism as two common conditions arising from dysfunction in the thyroid *** and timely diagnosis of these disorders is crucial for effective treatment and patient *** research introduces a comprehensive approach to improve the accuracy of thyroid disorder diagnosis through the integration of ensemble stacking and advanced feature selection *** forward feature selection,sequential backward feature elimination,and bidirectional feature elimination are investigated in this *** ensemble learning,random forest,adaptive boosting,and bagging classifiers are *** effectiveness of these techniques is evaluated using two different datasets obtained from the University of California Irvine-Machine Learning Repository,both of which undergo preprocessing steps,including outlier removal,addressing missing data,data cleansing,and feature *** experimentation demonstrates the remarkable success of proposed ensemble stacking and bidirectional feature elimination achieving 100%and 99.86%accuracy in identifying hyperthyroidism and hypothyroidism,*** enhancing detection accuracy,the ensemble stacking model also demonstrated a streamlined computational complexity which is pivotal for practical medical *** significantly outperformed existing studies with similar objectives underscoring the viability and effectiveness of the proposed *** research offers an innovative perspective and sets the platform for improved thyroid disorder diagnosis with broader implications for healthcare and patient well-being.

关键词： Ensemble learning random forests boosting dimensionality reduction machine learning smart healthcare computer aided diagnosis

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Impact of COVID-19 on liver transplant recipients: A nationwide cohort study evaluating hospitalization, transplant rejection, and inpatient mortality

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World Journal of Transplantation 2024年第2期14卷 62-75页

作者： Faisal Inayat Pratik Patel Hassam Ali Arslan Afzal Hamza Tahir Ahtshamullah Chaudhry Rizwan Ishtiaq Attiq ur rehman Kishan Darji muhammad Sohaib Afzal Gul Nawaz Alexa Giammarino Sanjaya K Satapathy Department of Internal Medicine Allama Iqbal Medical CollegeLahorePunjab 54550Pakistan Division of Gastroenterology Mather Hospital and Zucker School of Medicine at Hofstra UniversityPort JeffersonNY 11777United States Division of Gastroenterology and Hepatology East Carolina University Brody School of MedicineGreenvilleNC 27834United States Department of Internal Medicine Jefferson Einstein HospitalPhiladelphiaPA 19141United States Department of Internal Medicine St.Dominic's HospitalJacksonMS 39216United States Department of Internal Medicine Saint Francis Hospital and Medical CenterHartfordCT 06105United States Division of Hepatology Geisinger Wyoming Valley Medical CenterWilkes-BarrePA 18711United States Department of Internal Medicine Campbell University and Cape Fear Valley Medical CenterFayettevilleNC 28301United States Department of Internal Medicine North Shore University Hospital and Zucker School of Medicine at Hofstra UniversityManhassetNY 11030United States Division of Hepatology North Shore University Hospital and Zucker School of Medicine at Hofstra UniversityManhassetNY 11030United States

BACKGROUND The coronavirus disease 2019(COVID-19)pandemic has posed a major public health concern *** with comorbid conditions are at risk of adverse outcomes following *** organ transplant recipients with concurrent immunosuppression and comorbidities are more susceptible to a severe COVID-19 *** could lead to higher rates of inpatient complications and mortality in this patient ***,studies on COVID-19 outcomes in liver transplant(LT)recipients have yielded inconsistent *** To evaluate the impact of the COVID-19 pandemic on hospital-related outcomes among LT recipients in the United *** We conducted a retrospective cohort study using the 2019–2020 National Inpatient Sample *** with primary LT hospitalizations and a secondary COVID-19 diagnosis were identified using the International Classi-fication of Diseases,Tenth Revision coding *** primary outcomes included trends in LT hospitalizations before and during the COVID-19 *** outcomes included comparative trends in inpatient mortality and transplant rejection in LT *** A total of 15720 hospitalized LT recipients were *** 0.8% of patients had a secondary diagnosis of COVID-19 *** both cohorts,the median admission age was 57 *** linear trends for LT hospitalizations did not differ significantly before and during the pandemic(P=0.84).The frequency of in-hospital mortality for LT recipients increased from 1.7% to 4.4% between January 2019 and December *** to the pre-pandemic period,a higher association was noted between LT recipients and in-hospital mortality during the pandemic,with an odds ratio(OR)of 1.69[95% confidence interval(CI):1.55-1.84),Puring the COVID-19 pandemic had a higher associ

关键词： Liver transplant recipients Solid organ transplantation COVID-19 Hospitalization Transplant rejection Mortality

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