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Analyzing Arabic Twitter-Based Patient Experience Sentiments Using Multi-Dialect Arabic Bidirectional Encoder Representations from Transformers

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Computers, Materials & Continua 2023年第7期76卷 195-220页

作者： sarab almuhaideb Yasmeen AlNegheimish Taif AlOmar Reem AlSabti Maha AlKathery Ghala AlOlyyan Department of Computer Science College of Computer and Information SciencesKing Saud UniversityP.O.Box 266Riyadh 11362Saudi Arabia

Healthcare organizations rely on patients’feedback and experiences to evaluate their performance and services,thereby allowing such organizations to improve inadequate services and address any *** to the literature,social networks and particularly Twitter are effective platforms for gathering public ***,recent studies have used natural language processing to measure sentiments in text segments collected from Twitter to capture public opinions about various sectors,including *** present study aimed to analyze Arabic Twitter-based patient experience sentiments and to introduce an Arabic patient experience *** authors collected 12,400 tweets from Arabic patients discussing patient experiences related to healthcare organizations in Saudi Arabia from 1 January 2008 to 29 January *** tweets were labeled according to sentiment(positive or negative)and sector(public or private),and thereby the Hospital Patient Experiences in Saudi Arabia(HoPE-SA)dataset was produced.A simple statistical analysis was conducted to examine differences in patient views of healthcare *** authors trained five models to distinguish sentiments in tweets automatically with the following schemes:a transformer-based model fine-tuned with deep learning architecture and a transformer-based model fine-tuned with simple architecture,using two different transformer-based embeddings based on Bidirectional Encoder Representations from Transformers(BERT),Multi-dialect Arabic BERT(MAR-BERT),and multilingual BERT(mBERT),as well as a pretrained word2vec model with a support vector machine *** is the first study to investigate the use of a bidirectional long short-term memory layer followed by a feedforward neural network for the fine-tuning of *** deep-learning fine-tuned MARBERT-based model—the authors’best-performing model—achieved accuracy,micro-F1,and macro-F1 scores of 98.71%,98.73%,and 98.63%,respectively.

关键词： Sentiment analysis patient experience healthcare Twitter MARBERT bidirectional long short-term memory support vector machine transformer-based learning deep learning

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Impact of preprocessing on medical data classification

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Frontiers of Computer Science 2016年第6期10卷 1082-1102页

作者： sarab almuhaideb Mohamed El Bachir MENAI Computer Science Department College of Computer and Information Sciences Prince Sultan University Riyadh 11586 Saudi Arabia

The significance of the preprocessing stage in any data mining task is well known. Before attempting medical data classification, characteristics of medical datasets, including noise, incompleteness, and the existence of multiple and possibly irrelevant features, need to be addressed. In this paper, we show that selecting the right combination of prepro- cessing methods has a considerable impact on the classification potential of a dataset. The preprocessing operations con- sidered include the discretization of numeric attributes, the selection of attribute subset（s）, and the handling of missing values. The classification is performed by an ant colony optimization algorithm as a case study. Experimental results on 25 real-world medical datasets show that a significant relative improvement in predictive accuracy, exceeding 60% in some cases, is obtained.

关键词： classification ant colony optimization medical data classification preprocessing feature subset selection,discretization

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Deep Learning Enabled Intelligent Healthcare Management System in Smart Cities Environment

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Computers, Materials & Continua 2023年第2期74卷 4483-4500页

作者： Hanan Abdullah Mengash Lubna A.Alharbi Saud S.Alotaibi sarab almuhaideb Nadhem Nemri Mrim M.Alnfiai Radwa Marzouk Ahmed S.Salama Mesfer Al Duhayyim Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science College of Computers and Information TechnologyTabuk UniversityTabuk71491Saudi Arabia Department of Information Systems College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Computer Science College of Computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia Department of Information Systems College of Science and Arts at MuhayelKing Khalid UniversitySaudi Arabia Department of Information Technology College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Department of Electrical Engineering Faculty of Engineering&TechnologyFuture University in EgyptNew Cairo11845Egypt Department of Computer Science College of Sciences and Humanities-AflajPrince Sattam bin Abdulaziz UniversitySaudi Arabia

In recent times,cities are getting smart and can be managed effectively through diverse architectures and *** cities have the ability to support smart medical systems that can infiltrate distinct events(i.e.,smart hospitals,smart homes,and community health centres)and scenarios(e.g.,rehabilitation,abnormal behavior monitoring,clinical decision-making,disease prevention and diagnosis postmarking surveillance and prescription recommendation).The integration of Artificial Intelligence(AI)with recent technologies,for instance medical screening gadgets,are significant enough to deliver maximum performance and improved management services to handle chronic *** latest developments in digital data collection,AI techniques can be employed for clinical decision making *** the other hand,Cardiovascular Disease(CVD)is one of the major illnesses that increase the mortality rate across the ***,wearables can be employed in healthcare systems that instigate the development of CVD detection and *** this motivation,the current study develops an Artificial Intelligence Enabled Decision Support System for CVD Disease Detection and Classification in e-healthcare environment,abbreviated as AIDSS-CDDC *** proposed AIDSS-CDDC model enables the Internet of Things(IoT)devices for healthcare data ***,the collected data is saved in cloud server for *** by,training 4484 CMC,2023,vol.74,no.2 and testing processes are executed to determine the patient’s health *** accomplish this,the presented AIDSS-CDDC model employs data preprocessing and Improved Sine Cosine Optimization based Feature Selection(ISCO-FS)*** addition,Adam optimizer with Autoencoder Gated RecurrentUnit(AE-GRU)model is employed for detection and classification of *** experimental results highlight that the proposed AIDSS-CDDC model is a promising performer compared to other existing models.

关键词： Smart cities e-healthcare decision support system cardiovascular disease deep learning feature selection

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IWD-Miner: A Novel Metaheuristic Algorithm for Medical Data Classification

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Computers, Materials & Continua 2021年第2期66卷 1329-1346页

作者： sarab almuhaideb Reem BinGhannam Nourah Alhelal Shatha Alduheshi Fatimah Alkhamees Raghad Alsuhaibani Department of Computer Science College of Computer and Information SciencesKing Saud UniversityRiyadh11362Saudi Arabia

Medical data classification(MDC)refers to the application of classification methods on medical *** work focuses on applying a classification task to medical datasets related to specific diseases in order to predict the associated diagnosis or *** gain experts’trust,the prediction and the reasoning behind it are equally ***,we confine our research to learn rule-based models because they are transparent and *** approach to MDC involves the use of metaheuristic(MH)*** we report on the development and testing of a novel MH algorithm:*** algorithm can be viewed as a fusion of Intelligent Water Drops(IWDs)and AntMiner+.It was subjected to a four-stage sensitivity analysis to optimize its *** this purpose,21 publicly available medical datasets were used from the Machine Learning Repository at the University of California ***,there were only limited differences in performance between IWDMiner variants which is suggestive of its ***,using the same 21 datasets,we compared the performance of the optimized IWD-Miner against two extant algorithms,AntMiner+and *** experiments showed that both rival algorithms are considered comparable in the effectiveness to IWD-Miner,as confirmed by the Wilcoxon nonparametric statistical *** suggest that IWD-Miner is more efficient than AntMiner+as measured by the average number of fitness evaluations to a solution(1,386,621.30 vs.2,827,283.88 fitness evaluations,respectively).J48 exhibited higher accuracy on average than IWD-Miner(79.58 vs.73.65,respectively)but produced larger models(32.82 leaves vs.8.38 terms,respectively).

关键词： Ant colony optimization AntMiner+ IWDs IWD-Miner J48 medical data classification metaheuristic algorithms swarm intelligence

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Credit Card Fraud Detection Using Improved Deep Learning Models

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Computers, Materials & Continua 2024年第1期78卷 1049-1069页

作者： Sumaya S.Sulaiman Ibraheem Nadher sarab M.Hameed Computer Science Department Al-Mustansiriya UniversityBaghdad10001Iraq Computer Science Department University of BaghdadBaghdad10001Iraq Faculty of Basic Education Al-Mustansiriya UniversityBaghdad10001Iraq

Fraud of credit cards is a major issue for financial organizations and *** fraudulent actions become more complex,a demand for better fraud detection systems is *** learning approaches have shown promise in several fields,including detecting credit card ***,the efficacy of these models is heavily dependent on the careful selection of appropriate *** paper introduces models that integrate deep learning models with hyperparameter tuning techniques to learn the patterns and relationships within credit card transaction data,thereby improving fraud *** deep learning models:AutoEncoder(AE),Convolution Neural Network(CNN),and Long Short-Term Memory(LSTM)are proposed to investigate how hyperparameter adjustment impacts the efficacy of deep learning models used to identify credit card *** experiments conducted on a European credit card fraud dataset using different hyperparameters and three deep learning models demonstrate that the proposed models achieve a tradeoff between detection rate and precision,leading these models to be effective in accurately predicting credit card *** results demonstrate that LSTM significantly outperformed AE and CNN in terms of accuracy(99.2%),detection rate(93.3%),and area under the curve(96.3%).These proposed models have surpassed those of existing studies and are expected to make a significant contribution to the field of credit card fraud detection.

关键词： Card fraud detection hyperparameter tuning deep learning autoencoder convolution neural network long short-term memory resampling

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The Influence of Job Rotation on Employees Performance in the Syrian Nour Foundation

The Influence of Job Rotation on Employees Performance in th...

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作者： sarab ALAFLAQ 湖南大学

学位级别：硕士

工作轮换是世界各地组织用来提高员工绩效的一种实践。工作轮换的概念包括定期将员工从组织内的一个工作岗位调动到另一个工作岗位,使员工可以接触不同的职能领域并发展新的技能。工作轮换被视为建立高技能、高动力的员工队伍的有力工具... 详细信息

工作轮换是世界各地组织用来提高员工绩效的一种实践。工作轮换的概念包括定期将员工从组织内的一个工作岗位调动到另一个工作岗位,使员工可以接触不同的职能领域并发展新的技能。工作轮换被视为建立高技能、高动力的员工队伍的有力工具,这可以促进组织的成功。本案例研究探讨了工作轮换对叙利亚Nour基金会员工绩效的影响。工作轮换是许多组织常见的实践手段,旨在发展员工的技能、增加他们的工作满意度和提高他们的绩效。在本研究中,我们通过向与Nour基金会有关系的人分发问卷进行了实证研究。研究人口包括Nour基金会不同管理层级的200名员工。使用社会科学统计软件包(SPSS)对数据进行了分析和整理。使用描述性统计方法,包括百分比和频率表,对数据进行总结。此外,进行了可靠性分析,使用Cronbach's alpha进行有效性分析。为测试假设模型并确定独立变量对依赖变量的影响,对数据进行了相关和回归分析。此外,本研究使用结构方程模型(SEM)作为收集数据的统计技术。研究结果表明,工作轮换对员工绩效有积极影响。具体来说,经历工作轮换的员工报告的工作满意度更高,动力增加,绩效改善。此外,研究发现,工作轮换对员工技能和知识的发展有显著影响,最终导致了绩效的提高。研究得出结论,工作轮换是提高员工绩效的有效策略,并建议组织考虑实施工作轮换计划以改善员工绩效。

关键词：工作轮换员工绩效工作满意度技能、知识、动机叙利亚

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Generalized Second Law of Thermodynamics in Parabolic LTB Inhomogeneous Cosmology

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Communications in Theoretical Physics 2015年第11期64卷 597-604页

作者： A.Sheykhi H.Moradpour K.Rezazadeh sarab B.Wang Physics Department and Biruni Observatory College of SciencesShiraz University Research Institute for Astronomy and Astrophysics of Maragha(RIAAM) Department of Physics University of Kurdistan INPAC and Department of Physics Shanghai Jiao Tong University

We study thermodynamics of the parabolic Lemaitre-Tolman-Bondi(LTB) cosmology supported by a perfect Suid *** model is the natural generalization of the Sat Friedmann-Robertson-Walker(FRW) universe,and describes an inhomogeneous universe with spherical *** reviewing some basic equations in the parabolic LTB cosmology,we obtain a relation for the deceleration parameter in this *** also obtain a condition for which the universe undergoes an accelerating phase at the present *** use the first law of thermodynamics on the apparent horizon together with the Einstein field equations to get a relation for the apparent horizon entropy in LTB *** find out that in LTB model of cosmology,the apparent horizon's entropy could be feeded by a term,which incorporates the effects of the *** consider this result and get a relation for the total entropy evolution,which is used to examine the generalized second law of thermodynamics for an accelerating *** also verify the validity of the second law and the generalized second law of thermodynamics for a universe filled with some kinds of matters bounded by the event horizon in the framework of the parabolic LTB model.

关键词： parabolic LTB cosmology thermodynamics entropy gen

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SARS-CoV-2, surgeons and surgical masks

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World Journal of Clinical Cases 2021年第10期9卷 2170-2180页

作者： Mohammad Ibrahim Khalil Gouri Rani Banik sarab Mansoor Amani S Alqahtani Harunor Rashid Department of Surgery Dhaka Medical College HospitalDhaka 1000Bangladesh Clinical Research Unit The Department of MedicineUniversity of New South WalesSydney 2217New South WalesAustralia National Centre for Immunisation Research and Surveillance The Children’s Hospital at Westmead and the University of SydneyWestmead 2145New South WalesAustralia The University of Sydney School of Pharmacy Faculty of Medicine and HealthThe University of SydneySydney 2006New South WalesAustralia Research Department Saudi Food and Drug AuthorityRiyadh 13312Saudi Arabia National Centre for Immunisation Research and Surveillance The Children's Hospital at Westmeadand the University of SydneyWestmead 2145New South WalesAustralia Discipline of Child and Adolescent Health the Faculty of Medicine and HealthThe University of SydneySydney 2145New South WalesAustralia Marie Bashir Institute for Infectious Diseases and Biosecurity School of Biological Sciences and Sydney Medical SchoolThe University of SydneyWestmead 2145New South WalesAustralia

The exact risk association of coronavirus disease 2019(COVID-19)for surgeons is not quantified which may be affected by their risk of exposure and individual *** objective of this review is to quantify the risk of COVID-19 among surgeons,and explore whether facemask can minimise the risk of COVID-19 among surgeons.A systematised review was carried out by searching MEDLINE to locate items on severe acute respiratory syndrome coronavirus 2 or COVID-19 in relation to health care workers(HCWs)especially those work in surgical specialities including surgical nurses and ***,systematic reviews that assessed the effectiveness of facemask against viral respiratory infections,including COVID-19,among HCWs were *** from identified articles were abstracted,synthesised and *** primary studies that provided data on severe acute respiratory syndrome coronavirus 2 infection or experience among surgeons and 11 systematic reviews that provided evidence of the effectiveness of facemask(and other personal protective equipment)were *** the risk of COVID-19 could not be quantified precisely among surgeons,about 14%of HCWs including surgeons had COVID-19,there could be variations depending on *** was found to be somewhat protective against COVID-19,but the HCWs’compliance was highly variable ranging from zero to 100%.Echoing surgical societies’guidelines we continue to recommend facemask use among surgeons to prevent COVID-19.

关键词： COVID-19 Health care worker Personal protective equipment SARS-CoV-2 Surgeon Surgical mask

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The Isolation of Vibrio cholera and Other Enteric Bacteria with Molecular Characterization of Vibrio cholera during the Outbreak of Baghdad/Iraq in 2015

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Advances in Microbiology 2016年第9期6卷 699-715页

作者： sarab K. Jameel Mostafa A. Shafek Ali M. Abdulmohsen Nadira S. Mohamed Sarmad R. Naji Tuhama T. Mohammed AL-Yarmouk Teaching Hospital Baghdad Iraq Department of Gene Bank University of AL-Nahrain Baghdad Iraq

Vibrio cholera, causing acute watery diarrhea known as cholera disease, affects all ages and both genders. Cholera infection outbreaks in Iraq have been reported for several years. The recent cholera outbreak, emerged throughout 2015, was investigated using bacteriological laboratory tests, singleplex and multiplex PCR technique for the detection of V. cholera from stool samples. Furthermore the toxigenic potential coupled with the antibiotic susceptibility test for cholera and other bacteria were also investigated. The stool samples were collected from 5698 patients admitted to Al-Yarmouk Teaching hospital and health care centers in Baghdad/Al-Karkh, Iraq, from the 1st of August to the 30th of December 2015. The V. cholera was isolated from 194 cases (3.4% of the cases age between 21 - 50 years). In addition, other enteric infections: Salmonellosis and Shigellosis 7 and 21 respectively, protozoan parasite Giardia lamblia and Entamoeba histolytica 2 and 43 cases respectively were also reported. High percentage of V. cholera infection was detected in October (122 cases, 62.8%), compared with other enteric infections that show high percentage of diarrheal disease in September and November. The results have confirmed that the cholera outbreak was caused by V. cholera O1, biotype El Tor, and serotype Inaba. Seven virulence genes were identified ctxA, toxR, zot, ace, rfbO1, tcpA and ompW. Moreover, the cholera isolated strains were found sensitive to most antibiotic but resistant to nalidixic acid.

关键词： V. cholera Enteric Bacteria Diarrhea Outbreak Virulence Factor Genes Molecular Identification Antimicrobial Sensitivity Test

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Hybrid Features for an Arabic Word Recognition System

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Computer Technology and Application 2012年第10期3卷 685-691页

作者： Mehmmood A. Abd sarab Al Rubeaai George Paschos School of Electrical and Computer Engineering Windsor University Windsor N9P 3P4 Canada Nth Research Athens 18547 Greece

This research proposes and implements an Arabic Sub-Words Recognition System (ASWR). The system focuses on employing a combination of statistical and structural features to provide complete pattern"s description and enhances the recognition rate. Support Vector Machines (SVMs) is utilized as a promising pattern recognition tool. In addition to that, the problems of dots and holes are solved in a completely different way from the ones previously employed. The proposed system proceeds in several phases as follows: (1) image acquisition, (2) binarisation, (3) morphological processing, (4) feature extraction, which includes statistical features, i. e., moment invariants, and structural features, i. e., dot number, dot position, and number of holes, features, and (5) classification, using multi-class SVMs and applying a one-against-all technique. The proposed system has been tested using different sets of words and subwords and has achieved a nearly 98.90% recognition rate. Comparative results with NNs are also presented.

关键词：识别系统阿拉伯支持向量机混合语词人工神经网络特征提取统计功能

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