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Cognitive Computing-Based Mammographic Image Classification on an Internet of Medical

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Computers, Materials & Continua 2022年第8期72卷 3945-3959页

作者： Romany F.mansour Maha M.althobaiti Department of Mathematics Faculty of ScienceNew Valley UniversityEl-Kharga72511Egypt Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia

Recently,the Internet of Medical Things(IoMT)has become a research hotspot due to its various applicability in medical ***,the data analysis and management in IoMT remain challenging owing to the existence of a massive number of devices linked to the server environment,generating a massive quantity of h.althcare *** such cases,cognitive computing can be employed that uses many intelligent technologies-machine learning(ML),deep learning(DL),artificial intelligence(AI),natural language processing(NLP)and others-to comprehend data ***,breast cancer(BC)has been found to be a major cause of mortality among ladies *** detection and classification of BC using digital mammograms can decrease the mortality *** paper presents a novel deep learning-enabled multi-objective mayfly optimization algorithm(DLMOMFO)for BC diagnosis and classification in the IoMT *** goal of this paper is to integrate deep learning(DL)and cognitive computing-based techniques for e-h.althcare applications as a part of IoMT technology to detect and classify *** proposed DL-MOMFO algorithm involved Adaptive Weighted Mean Filter(AWMF)-based noise removal and contrast-limited adaptive histogram equalisation(CLAhE)-based contrast improvement techniques to improve the quality of the digital *** addition,a U-Net architecture-based segmentation method was utilised to detect diseased regions in the ***,a SqueezeNet-based feature extraction and a fuzzy support vector machine(FSVM)classifier were used in the presented *** enhance the diagnostic performance of the presented method,the MOMFO algorithm was used to effectively tune the parameters of the SqueezeNet and FSVM *** DL-MOMFO technique was tested on the MIAS database,and the experimental outcomes revealed that the DL-MOMFO technique outperformed existing techniques.

关键词： Cognitive computing breast cancer digital mammograms image processing internet of medical things smart h.althcare

Association of E-cadherin (CDh1) gene polymorphisms and gastric cancer risk

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World Journal of Gastroenterology 2010年第27期16卷 34332-3436页

作者： mansour S al-Moundhri Manal al-Khanbashi Mohammed al-Kindi Maryam al-Nabhani Ikram A Burney Abdulaziz al-Farsi Bassim al-Bahrani Medical Oncology Unit Department of MedicineCollege of Medicine and Health SciencesSultan Qaboos University Department of Clinical Genetics College of Medicine and Health SciencesSultan Qaboos University Department of Biochemistry College of Medicine and Health SciencesSultan Qaboos University National Oncology Center Royal Hospital

AIM:To investigate the associations between CDh1 gene polymorphisms and gastric cancer(GC) risk ***:We analyzed four CDh1 polymorphisms(+54 T>C,-160 C>A,-616 G>C,-3159 T>C) in an Omani population,by extraction of genomic DNA from the peripheral blood of 192 patients with GC and 170 control participants and performed CDh1 genotyping using DNA ***:CDh1-160-AA genotype was associated with an increased risk of GC(OR = 3.6,95% CI:1.1-11.8)(P = 0.03).There was no significant association between the other polymorphisms and GC *** haplotype analysis of +54 T>C,-160 C>A,-616 G>C,-3159 T>C genotypes revealed that the OR of CCGC and CAGC haplotypes was 1.5(95% CI:0.7-3.5) and 1.5(95% CI:0.2-3.0),but did not reach statistical ***:The current study suggests that the-160 AA genotype was associated with an increased risk of GC in Oman.

关键词： Gastric cancer Polymorphism CDh1

The Lanthanide Tetrad Effect in Argillic alteration: An Example from the Jizvan District, Northern Iran

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Acta Geologica Sinica(English Edition) 2018年第4期92卷 1468-1485页

作者： ali ABEDINI mansour REZAEI AZIZI ali Asghar CalAGARI Department of Geology Faculty of Sciences Urmia University Department of Earth Sciences Faculty of Natural Sciences University of Tabriz

Intrusion of quartz-monzodioritic igneous bodies of Oligocene age into Eocene lithic crystal tufts and trachy-basalts resulted in the occurrence of a widespread argillic alteration zone in the Jizvan district （northern Iran）. Mineralogically, the argillie alteration zone includes minerals such as kaolinite, quartz, smectite, pyrophyllite, muscovite-illite, alunite, rutile, calcite, feldspar, chlorite, hematite and goethite. Therefore, the non-ChARAC behaviour for trace elements in the argillic samples is reflected in the non-chondritic Y/ho and Zr/hf ratios and the irregular REE patterns, which appear related to the tetrad effect phenomenon. The chondrite-normalized REE distribution patterns indicate both concave （W-shaped） and convex （M-shaped） tetrad effects in the argillic samples. Based on the field evidence and the results from geochemical studies, it can be concluded that the samples from the argillic alteration zone having high fourth tetrad effect values （〉0.30） were developed in the fault and breccia zones. The results indicate that factors such as preferential scavenging by Mn-oxides, crystallization of clay minerals, fluid-rock interaction, overprint of hypogene mineral assemblage by supergene ones, and the structural control, have all played an important role in the occurrence of tetrad effects in samples of the argillic zone in the Jizvan district.

关键词： REE geochemistry tetrad effect argillic alteration Jizvan Iran

Aflatoxins,hepatocellular carcinoma and public h.alth

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World Journal of Gastroenterology 2013年第10期19卷 1508-1512页

作者： Arvin Magnussen mansour A Parsi Sandefjord high School 3228 SandefjordNorway Section for Therapeutic and Pancreatobiliary Endoscopy Digestive Disease InstituteCleveland ClinicClevelandOH 44195United States

hepatocellular carcinoma(hCC) is one of the leading causes of cancer deaths worldwide,primarily affecting populations in the developing ***,a food contaminant produced by the fungi Aspergillus flavus and Aspergillus parasiticus,is a known human carcinogen that has been shown to be a causative agent in the pathogenesis of *** can affect a wide range of food commodities including corns,oilseeds,spices,and tree nuts as well as milk,meat,and dried *** factors affect the growth of Aspergillus fungi and the level of aflatoxin contamination in *** stress is one of the factors that increase susceptibility of plants to Aspergillus and thus aflatoxin contamination.A recent drought is thought to be responsible for finding of trace amounts of aflatoxin in some of the corn harvested in the United *** it's too soon to know whether aflatoxin will be a significant problem,since United States is the world's largest corn producer and exporter,this has raised alarm *** regulations and testing of finished foods and feeds in the United States should prevent a major h.alth scare,and prevent human exposure to deleterious levels of ***,such regulations and testing are not in place in many *** purpose of this editorial is to summarize the current knowledge on association of aflatoxin and hCC,encourage future research and draw attention to this global public h.alth issue.

关键词： Aflatoxins hepatocellular carcinoma Environmental h.alth Food safety Public h.alth

REE Tetrad Effect as a Powerful Indicator of Formation Conditions of Karst Bauxites: A Case Study of the Shahindezh Deposit, NW Iran

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Acta Geologica Sinica(English Edition) 2019年第4期93卷 912-927页

作者： ali ABEDINI mansour REZAEI AZIZI ali Asghar CalAGARI Department of Geology Faculty of SciencesUrmia University*** UrmiaIran Department of Earth Sciences Faculty of Natural SciencesUniversity of Tabriz*** TabrizIran

Study of the concentration of major,trace,and rare earth elements(REE)in the Shahindezh karst bauxite deposit,northwestern Iran clarifies the relationship of the tetrad effect with geochemical parameters in the bauxite *** existence of irregular curves in the chondrite-normalized REE patterns as well as non-ChARAC behavior of geochemically isovalent pairs(Y/ho)are related to the tetrad *** meaningful positive correlation between the sizes of the calculated T3 tetrad effect and some geochemical factors such as Y/ho,ΣREE,La/Y,(La/Yb)N,and(LREE/hREE)N as well as some major oxides-based parameters like al2O3+LOI/SiO2+Fe2O3,al2O3/Fe2O3,al2O3+LOI,IOL,and SiO2+Fe2O3indicate that the studied bauxite horizon was likely deposited by different(acidic and/or alkalic)solutions at different *** lower part of the studied horizon with a thickness of^4.7 m displays alkali characteristics whereas the upper parts of the horizon with a thickness of^5.3 m are characterized by more acidic *** results are fully supported by the co-occurrence of convex-concave tetrad effect curves in the chondrite-normalized REE ***,the tetrad effect phenomenon used in this study has proved to be a good and reliable geochemical proxy to assess the conditions of the depositional environment in the Shahindezh bauxite ores.

关键词： Geochemistry REE Tetrad effect Karst bauxite Shahindezh Iran

Natural Language Processing with Optimal Deep Learning Based Fake News Classification

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Computers, Materials & Continua 2022年第11期73卷 3529-3544页

作者： Sara Aalthubiti Fayadh.alenezi Romany F.mansour Department of Computer Science College of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia Department of Electrical Engineering College of EngineeringJouf UniversitySaudi Arabia Department of Mathematics Faculty of ScienceNew Valley UniversityEl-Kharga72511Egypt

The recent advancements made in World Wide Web and social networking have eased the spread of fake news among people at a faster *** most of the times,the intention of fake news is to misinform the people and make manipulated societal *** spread of low-quality news in social networking sites has a negative influence upon people as well as the *** order to overcome the ever-increasing dissemination of fake news,automated detection models are developed using Artificial Intelligence(AI)and Machine Learning(ML)*** latest advancements in Deep Learning(DL)models and complex Natural Language Processing(NLP)tasks make the former,a significant solution to achieve Fake News Detection(FND).In this background,the current study focuses on design and development of Natural Language Processing with Sea Turtle Foraging Optimizationbased Deep Learning Technique for Fake News Detection and Classification(STODL-FNDC)*** aim of the proposed STODL-FNDC model is to discriminate fake news from legitimate news in an effectual *** the proposed STODL-FNDC model,the input data primarily undergoes pre-processing and Glove-based word ***,STODL-FNDC model employs Deep Belief Network(DBN)approach for detection as well as classification of fake ***,STO algorithm is utilized after adjusting the hyperparameters involved in DBN model,in an optimal *** novelty of the study lies in the design of STO algorithm with DBN model for *** order to improve the detection performance of STODL-FNDC technique,a series of simulations was carried out on benchmark *** experimental outcomes established the better performance of STODL-FNDC approach over other methods with a maximum accuracy of 95.50%.

关键词： Natural language processing text mining fake news detection deep belief network machine learning evolutionary algorithm

Steganography-Based Transmission of Medical Images Over Unsecure Network for Telemedicine Applications

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Computers, Materials & Continua 2021年第9期68卷 4069-4085页

作者： Romany F.mansour Moheb R.Girgis Department of Mathematics Faculty of ScienceNew Valley UniversityEl-Kharga72511Egypt Department of Computer Science Faculty of ScienceMinia UniversityEl-MiniaEgypt

Steganography is one of the best techniques to hide secret *** steganography methods are available that use an image as a cover object,which is called image *** image steganography,the major features are the cover object quality and hiding data *** to poor image quality,attackers could easily hack the secret ***,the hidden data quantity should be improved,while keeping stego-image quality *** main aim of this study is combining several steganography techniques,for secure transmission of data without leakage and unauthorized *** this paper,a technique,which combines various steganographybased techniques,is proposed for secure transmission of secret *** the pre-processing step,resizing of cover image is performed with Pixel Repetition Method(PRM).Then DES(Data Encryption Standard)algorithm is used to encrypt secret data before embedding it into cover *** encrypted data is then converted to hexadecimal *** is followed by embedding using Least Signification Bit(LSB)in order to hide secret data inside the cover ***,image de-noising using Convolutional Neural Network(CNN)is used to enhance the cover image with hidden encrypted *** Zerotrees of Wavelet Transform is used to compress the image in order to reduce its *** are conducted to evaluate the performance of proposed combined steganography technique and results indicate that the proposed technique outperforms all existing *** achieves better PSNR,and encryption/decryption times,than existing methods for medical and other types of images.

关键词： Steganography secure data transmission CNN encryption telemedicine

NAT2 polymorphism in Omani gastric cancer patients-risk predisposition and clinicopathological associations

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World Journal of Gastroenterology 2007年第19期13卷 2697-2702页

作者： mansour S al-Moundhri Mohamed al-Kindi Maryam al-Nabhani Bassim al-Bahrani Ikram A Burney ali al-Madhani Shyam S Ganguly Misbah Tanira Medical Oncology Unit Department of Medicine College of Medicine and Health Sciences Sultan Qaboos University Sultanate of Oman Department of Biochemistry and Genetics Sultan Qaboos University Sultanate of Oman National Cancer Institute Royal Hospital Sultanate of Oman Department of Medicine Sohar Hospital Sultanate of Oman Department of Epidemiology and Medical Statistics Sultan Qaboos University Sultanate of Oman Department of Pharmacology Sultan Qaboos University Sultanate of Oman

AIM： To study whether N-acetyltransferase 2 （NAT2） genotypes and phenotypes are associated with increased risk factor for gastric cancer in Omani patients and to study the clinico-pathological correlations and the prognostic significance of NAT2. METhODS： Genomic DNA was extracted from peripheral blood of 100 gastric cancer patients and 100 control subjects. NAT2 genotyping was performed using DNA sequencing. The prognostic significance of NAT2 and other clinicopathological features was assessed by univariate and multivariate analyses. RESULTS： We observed no significant association between NAT2 genotypes and phenotypes and gastric cancer risk. The IVAT2 phenotype polymorphisms and gastric cancer risk predisposition were not modified by concomitant hpylori infection and smoking. There was no significant association between NAT2 and clinicopathological features, and NAT2 had no independent prognostic significance. CONCLUSION： In the current study, NAT2 genotypes and phenotypes are not associated with gastric cancer risk predisposition. Moreover NAT2 phenotypes had no clinicopathological associations or prognostic significance.

关键词： Gastric cancer Polymorphism NAT2 hpylori Arab Omani

Computer Vision with Machine Learning Enabled Skin Lesion Classification Model

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Computers, Materials & Continua 2022年第10期73卷 849-864页

作者： Romany F.mansour Sara A.althubiti Fayadh.alenezi Department of Mathematics Faculty of ScienceNew Valley UniversityEl-Kharga72511Egypt Department of Computer Science College of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia Department of Electrical Engineering College of EngineeringJouf UniversitySakaka72388Saudi Arabia

Recently,computer vision(CV)based disease diagnosis models have been utilized in various areas of *** the same time,deep learning(DL)and machine learning(ML)models play a vital role in the h.althcare sector for the effectual recognition of diseases using medical imaging *** study develops a novel computer vision with optimal machine learning enabled skin lesion detection and classification(CVOML-SLDC)*** goal of the CVOML-SLDC model is to determine the appropriate class labels for the test dermoscopic ***,the CVOML-SLDC model derives a gaussian filtering(GF)approach to pre-process the input images and graph cut segmentation is ***,firefly algorithm(FFA)with EfficientNet based feature extraction module is applied for effectual derivation of feature ***,naïve bayes(NB)classifier is utilized for the skin lesion detection and classification *** application of FFA helps to effectually adjust the hyperparameter values of the EfficientNet *** experimental analysis of the CVOML-SLDC model is performed using benchmark skin lesion *** detailed comparative study of the CVOML-SLDC model reported the improved outcomes over the recent approaches with maximum accuracy of 94.83%.

关键词： Skin lesion detection dermoscopic images machine learning deep learning graph cut segmentation EfficientNet