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Yield of alarm features in predicting significant endoscopic findings among hospitalized patients with dyspepsia

World Journal of Gastroenterology 2024年第26期30卷 3210-3220页

作者： Lama Ibrahim maamoun basheer Tawfik Khoury Wisam Sbeit Department of Internal Medicine Galilee Medical CenterNahariya 22001Israel Department of Gastroenterology Galilee Medical CenterNahariya 22001Israel Azrieli Faculty of Medicine Bar-Ilan UniversitySafed 1311502Israel

BACKGROUND Dyspepsia is a very prevalent upper gastrointestinal tract symptoms *** of these symptoms might arise from serious underlying diseases,so the promotion of evidence-based guidelines could potentially better align evaluation and *** To determine the value of alarm features as a predictive factor for significant endoscopic findings(SEFs)among hospitalized patients presenting with *** We conducted a retrospective case-control study including information about 6208 endoscopic procedures performed for hospitalized *** were divided into two groups,with and without SEFs,and compared to elucidate the ability of the different alarm features to predict *** During the study,605 patients fulfilled the inclusion *** the demographics and clinical characteristics of the two groups were compared,tachycardia(P<0.05),normocytic anemia,(P<0.05),leukocytosis(P<0.05),and hypoalbuminemia(P<0.05)documented on admission prior to endoscopy were strong predictors of *** the alarm features,upper gastrointestinal bleeding,persistent vomiting,odynophagia[odds ratio(OR)=3.81,P<0.05;OR=1.75,P=0.03;and OR=7.81,P=0.07,respectively]were associated with *** weight loss was strongly associated with malignancy as an endoscopic finding(OR=2.05;P<0.05).In addition,long-term use of anti-aggregate medications other than aspirin(P<0.05)was correlated to *** Novel predictors of SEFs were elucidated in this *** parameters could be used as an adjunctive in decision making regarding performing upper endoscopy in hospitalized patients with dyspepsia.

关键词： Dyspepsia Endoscopy Weight loss Anti-aggregate medications Persistent vomiting Odynophagia

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Smart Healthcare Activity Recognition Using Statistical Regression and Intelligent Learning

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Computers, Materials & Continua 2024年第1期78卷 1189-1205页

作者： K.Akilandeswari Nithya Rekha Sivakumar Hend Khalid Alkahtani Shakila basheer Sara Abdelwahab Ghorashi Department of Computer Sciences Government Arts College(Autonomous)Salem636007India Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia

In this present time,Human Activity Recognition(HAR)has been of considerable aid in the case of health monitoring and *** exploitation of machine learning with an intelligent agent in the area of health informatics gathered using HAR augments the decision-making quality and *** many research works conducted on Smart Healthcare Monitoring,there remain a certain number of pitfalls such as time,overhead,and falsification involved during ***,this paper proposes a Statistical Partial Regression and Support Vector Intelligent Agent Learning(SPR-SVIAL)for Smart Healthcare *** first,the Statistical Partial Regression Feature Extraction model is used for data preprocessing along with the dimensionality-reduced features extraction ***,the input dataset the continuous beat-to-beat heart data,triaxial accelerometer data,and psychological characteristics were acquired from IoT wearable *** attain highly accurate Smart Healthcare Monitoring with less time,Partial Least Square helps extract the dimensionality-reduced *** that,with these resulting features,SVIAL is proposed for Smart Healthcare Monitoring with the help of Machine Learning and Intelligent Agents to minimize both analysis falsification and *** evaluation is carried out for factors such as time,overhead,and false positive rate accuracy concerning several *** quantitatively analyzed results indicate the better performance of our proposed SPR-SVIAL method when compared with two state-of-the-art methods.

关键词： Internet of Things smart health care monitoring human activity recognition intelligent agent learning statistical partial regression support vector

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Ultralong hydroxyapatite-based forward osmosis membrane for freshwater generation

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Frontiers of Chemical Science and Engineering 2024年第9期18卷 37-49页

作者： Mohamed Gamal Gomaa Hamdy maamoun Abdel-Ghafar Francesco Galiano Francesca Russo Alberto Figoli El-Sayed Ali Abdel-Aal Abdel-Hakim Taha Kandil Bahaa Ahmed Salah Central Metallurgical Research and Development Institute(CMRDI) 11421 CairoEgypt Chemistry Department Faculty of ScienceHelwan University11795 CairoEgypt Institute on Membrane Technology(CNR-ITM) 87036 RendeItaly

Increasing global water shortages are accelerating the pace of membrane manufacturing,which generates many environmentally harmful *** challenges need a radical rethink of developing innovative membranes that can address freshwater production without generating environmentally harmful *** work utilized the synthesized ultra-long hydroxyapatite(UHA)by the solvothermal method using the green solvent oleic acid in preparing UHA-based forward osmosis *** membranes were developed using different loading ratios of graphene oxide(GO)by vacuum-assisted filtration *** prepared GO/UHA membranes were identified using X-ray diffraction,scanning electron microscope,Fourier-transform infrared spectroscopy,and X-ray photoelectron *** contact angle and pore size distribution were determined for the obtained GO/UHA *** obtained hierarchical porous structure in the prepared membranes with interconnected channels results in a stable water flux with reverse salt *** best water flux rate of 42±2 L·m^(–2)·h^(–1)was achieved using the 50 mg GO/UHA membrane,which is 3.3 times higher than the pristine membrane,and a reverse salt flux of 67 g·m^(-2)·h^(–1).The obtained results showed a promising capability of a new generation of sustainable inorganic-based membranes that can be utilized in freshwater generation by energy-efficient techniques such as forward osmosis.

关键词： forward osmosis ultra-long hydroxyapatite graphene oxide inorganic-based membrane

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Sepsis Prediction Using CNNBDLSTM and Temporal Derivatives Feature Extraction in the IoT Medical Environment

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Computers, Materials & Continua 2024年第4期79卷 1157-1185页

作者： Sapiah Sakri Shakila basheer Zuhaira Muhammad Zain Nurul Halimatul Asmak Ismail Dua’Abdellatef Nassar Manal Abdullah Alohali Mais Ayman Alharaki Department of Information Systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Kingdom of Saudi Arabia Department of Computer Science and Information Technology Applied CollegePrincess Nourah Bint Abdulrahman UniversityRiyadh11671Kingdom of Saudi Arabia

Background:Sepsis,a potentially fatal inflammatory disease triggered by infection,carries significant healthimplications *** detection is crucial as sepsis can rapidly escalate if left *** in deep learning(DL)offer powerful tools to address this ***:Thus,this study proposeda hybrid CNNBDLSTM,a combination of a convolutional neural network(CNN)with a bi-directional long shorttermmemory(BDLSTM)model to predict sepsis *** the proposed model provides a robustframework that capitalizes on the complementary strengths of both architectures,resulting in more accurate andtimelier ***:The sepsis prediction method proposed here utilizes temporal feature extraction todelineate six distinct time frames before the onset of *** time frames adhere to the sepsis-3 standardrequirement,which incorporates 12-h observation windows preceding sepsis *** models were trained usingthe Medical Information Mart for Intensive Care III(MIMIC-III)dataset,which sourced 61,522 patients with 40clinical variables obtained from the IoT medical *** confusion matrix,the area under the receiveroperating characteristic curve(AUCROC)curve,the accuracy,the precision,the F1-score,and the recall weredeployed to evaluate ***:The CNNBDLSTMmodel demonstrated superior performance comparedto the benchmark and other models,achieving an AUCROC of 99.74%and an accuracy of 99.15%one hour beforesepsis *** results indicate that the CNNBDLSTM model is highly effective in predicting sepsis onset,particularly within a close proximity of one ***:The results could assist practitioners in increasingthe potential survival of the patient one hour before sepsis onset.

关键词： Temporal derivatives hybrid deep learning predicting sepsis onset MIMIC III machine learning(ML) deep learning

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Marine Predators Algorithm with Deep Learning-Based Leukemia Cancer Classification on Medical Images

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Computer Modeling in Engineering & Sciences 2024年第10期141卷 893-916页

作者： Sonali Das Saroja Kumar Rout Sujit Kumar Panda Pradyumna Kumar Mohapatra Abdulaziz S.Almazyad Muhammed basheer Jasser Guojiang Xiong Ali Wagdy Mohamed Department of Computer Science&Engineering Gandhi Institute for TechnologyBPUTBhubaneswar752054India Department of Information Technology Vardhaman College of Engineering(Autonomous)Hyderabad501218TelanganaIndia Department of Electronic&Communication Engineering Vedang Institute of TechnologyBhubaneswar752010India Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia Department of Computing and Information Systems School of Engineering and TechnologySunway UniversityJalan UniversitiBandar SunwaySelangor Darul Ehsan47500Malaysia Research Centre for Human-Machine Collaboration(HUMAC) School of Engineering and TechnologySunway UniversityJalan UniversitiBandar SunwaySelangor Darul Ehsan47500Malaysia Guizhou Key Laboratory of Intelligent Technology in Power System College of Electrical EngineeringGuizhou UniversityGuiyang550025China Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Applied Science Research Center Applied Science Private UniversityAmman11931Jordan

In blood or bone marrow,leukemia is a form of cancer.A person with leukemia has an expansion of white blood cells(WBCs).It primarily affects children and rarely affects *** depends on the type of leukemia and the extent to which cancer has established throughout the *** leukemia in the initial stage is vital to providing timely patient *** image-analysis-related approaches grant safer,quicker,and less costly solutions while ignoring the difficulties of these invasive *** can be simple to generalize Computer vision(CV)-based and image-processing techniques and eradicate human *** researchers have implemented computer-aided diagnosticmethods andmachine learning(ML)for laboratory image analysis,hopefully overcoming the limitations of late leukemia detection and determining its *** study establishes a Marine Predators Algorithm with Deep Learning Leukemia Cancer Classification(MPADL-LCC)algorithm onMedical *** projectedMPADL-LCC system uses a bilateral filtering(BF)technique to pre-process medical *** MPADL-LCC system uses Faster SqueezeNet withMarine Predators Algorithm(MPA)as a hyperparameter optimizer for feature ***,the denoising autoencoder(DAE)methodology can be executed to accurately detect and classify leukemia *** hyperparameter tuning process using MPA helps enhance leukemia cancer classification *** results are compared with other recent approaches concerning various measurements and the MPADL-LCC algorithm exhibits the best results over other recent approaches.

关键词： Leukemia cancer medical imaging image classification deep learning marine predators algorithm

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Micelles as potential drug delivery systems for colorectal cancer treatment

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World Journal of Gastroenterology 2022年第25期28卷 2867-2880页

作者： Zaynab Fatfat maamoun Fatfat Hala Gali-Muhtasib Department of Biology American University of BeirutBeirut 11072020Lebanon Center for Drug Discovery American University of BeirutBeirut 11072020Lebanon

Despite the significant progress in cancer therapy,colorectal cancer(CRC)remains one of the most fatal malignancies *** is currently the mainstay therapeutic modality adopted for CRC ***,the long-term effectiveness of chemotherapeutic drugs has been hampered by their low bioavailability,non-selective tumor targeting mechanisms,non-specific biodistribution associated with low drug concentrations at the tumor site and undesirable side *** the last decade,there has been increasing interest in using nanotechnology-based drug delivery systems to circumvent these *** nanoparticles have been developed for delivering chemotherapeutic drugs among which polymeric micelles are attractive *** micelles are biocompatible nanocarriers that can bypass the biological barriers and preferentially accumulate in tumors via the enhanced permeability and retention *** can be easily engineered with stimuli-responsive and tumor targeting moieties to further ensure their selective uptake by cancer cells and controlled drug release at the desirable tumor *** have been shown to effectively improve the pharmacokinetic properties of chemotherapeutic drugs and enhance their safety profile and anticancer efficacy in different types of *** that combination therapy is the new strategy implemented in cancer therapy,polymeric micelles are suitable for multidrug delivery and allow drugs to act concurrently at the action site to achieve synergistic therapeutic *** also allow the delivery of anticancer genetic material along with chemotherapy drugs offering a novel approach for CRC ***,we highlight the properties of polymeric micelles that make them promising drug delivery systems for CRC *** also review their application in CRC chemotherapy and gene therapy as well as in combination cancer chemotherapy.

关键词： Polymeric micelles Drug delivery Colorectal cancer Chemotherapy Gene therapy Combination cancer therapy

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Biodegradation of p-cresol by aerobic granules in sequencing batch reactor

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Journal of Environmental Sciences 2012年第11期24卷 2012-2027页

作者： Farrukh basheer I.H.Farooqi Environmental Engineering Section Department of Civil EngineeringAligarh Muslim UniversityAligarh202002India

The cultivation of aerobic granules in sequencing batch reactor for the biodegradation of p-cresol was studied. The reactor was started with 100 mg/L of p-cresol. Aerobic granules first appeared within one month of start up. The granules were large and strong and had a compact structure. The diameter of stable granules was in the range of 1-5 mm. The integrity coefficient and granules density was found to be 96% and 1046 kg/m3, raspectively, The settling velocity of granules was found to be in the range of 2×10^-2-6×10^-7 m/sec. The aerobic granules were able to degrade p-cresol upto 800 mg/L at a removal efficiency of 88%. Specific p-cresol degradation rate in aerobic granules followed Haldane model for substrate inhibition, High specific p-cresol degradation rate up to 0,96 g pcresol/（g ***） were sustained upto p-cresol concentration of 400 mg/L, Higher removal efficiency, good settling characteristics of aerobic granules, makes sequencing batch reactor suitable for erLhaneing the microorganism potential for biodegradation of inhibitory compounds.

关键词： aerobic granules p-cresol sequencing batch reactor (SBR) haldane kinetics equation

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Sulfamic acid functionalized slag for effective removal of organic dye and toxic metal from the aqueous samples

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Chinese Journal of Chemical Engineering 2021年第5期34卷 306-318页

作者： Dauda Mohammed Muhammad HAl-Malack basheer Chanbasha Department of Civil and Environmental Engineering King Fahd University of Petroleum&MineralsDhahran 31261Saudi Arabia Department of Chemistry King Fahd University of Petroleum&MineralsDhahran 31262Saudi Arabia

Surface functionalization of blast furnace slag with sulfamic acid(a zwitterion)was performed for the removal of Cr^(3+)and methylene blue dye(MB)from water *** slag functionalization process was optimized using Response Surface Methodology *** analysis of the parameters that include the sulfamic acid amount(A),reaction time(B),and temperature(C)revealed that(A)increase had a negative effect on the adsorption of both pollutants by the zwitterion slag,whereas(B)and(C)increase presented a positive *** the optimum condition of 2 g sulfamic acid amount,50 min reaction time and 37℃ temperature,the prepared slag showed a removal efficiency of more than 90% for both Cr^(3+)and *** characterization by SEM/EDS,FTIR,XPS and surface area analyser,showed an improvement in surface properties and the incorporation of zwitterionic NH^(2+)and S=O groups of sulfamic *** isotherm and kinetic studies conducted with the zwitterion slag showed the adsorption process was suited to Freundlich isotherm model and pseudo-second-order kinetic *** thermodynamic study conducted revealed the spontaneity of the process based on the calculated negativeΔG(Gibb’s free energy)*** prepared zwitterion slag offered easy regeneration with dilute HCl solution and showed a considerable removal(Cr^(3+):65% and MB:80%)for both pollutants even after 3 cycles of usage.

关键词： Functional groups Optimization Zwitterion Adsorption Waste treatment Industrial waste

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Energy transfer in solid-state dye lasers based on methyl methacrylate co-doped with sulforhodamine B and crystal violet

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Chinese Physics B 2013年第11期22卷 319-324页

作者： R.G.Geethu Mani M.basheer Ahamed Department of Physics KCG College of Technology Research Centre Bharathiar University Department of Physics B.S. Abdur Rahman University

Laser action in methyl methacrylate （MMA） co-doped with sulforhodamine B and crystal violet dyes was investi- gated. The dye mixture was incorporated into a solid polymeric matrix and was pumped by a 532-nm Nd：YAG laser. Distributed feedback dye laser （DFDL） action was induced in the dye mixture using a prism arrangement both in the donor and acceptor regions by an energy transfer mechanism. Theoretically, the characteristics of acceptor and donor DFDLs, and the dependence of their pulse widths and output powers on acceptor-donor concentrations and pump power, were studied. Experimentally, the output energy of DFDL was measured at the emission peaks of donor and acceptor dyes for different pump powers and different acceptor-donor concentrations. Tuning of the output wavelength was achieved by varying the period of the gain modulation of the laser medium. The laser wavelength showed continuous tunability from 563 nm to 648 nm.

关键词： sulforhodamine B crystal violet distributed feedback dye laser solid state distributed feedbackdye laser

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Prediction System for Diagnosis and Detection of Coronavirus Disease-2019(COVID-19):A Fuzzy-Soft Expert System

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Computer Modeling in Engineering & Sciences 2023年第6期135卷 2715-2730页

作者： Wencong Liu Ahmed Mostafa Khalil Rehab basheer Yong Lin School of Science Xi’an Technological UniversityXi’an710021China Department of Mathematics Faculty of ScienceAl-Azhar UniversityAssiut71524Egypt Department of Mathematics Faculty of ScienceAssiut UniversityAssiut71516Egypt Respiratory Department of Nanjing Chest Hospital Affiliated to Southeast University Nanjing210000China

In early December 2019,a new virus named“2019 novel coronavirus(2019-nCoV)”appeared in Wuhan,*** disease quickly spread worldwide,resulting in the COVID-19 *** the currentwork,we will propose a novel fuzzy softmodal(i.e.,fuzzy-soft expert system)for early detection of *** construction of the fuzzy-soft expert systemconsists of five *** exploratory study includes sixty patients(i.e.,fortymales and twenty females)with symptoms similar to COVID-19 in(Nanjing Chest Hospital,Department of Respiratory,China).The proposed fuzzy-soft expert systemdepended on five symptoms of COVID-19(i.e.,shortness of breath,sore throat,cough,fever,and age).We will use the algorithm proposed by Kong et *** detect these patients who may suffer from *** this way,the present system is beneficial to help the physician decide if there is any patient who has COVID-19 or ***,we present the comparison between the present system and the fuzzy expert system.

关键词： Coronavirus disease-2019(COVID-19) fuzzy-soft expert system fuzzy expert system diagnosed results

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