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Computers, Materials & Continua 2024年第4期79卷 963-981页

作者： Muhammad Umar Nasir Omar Kassem Khalil Karamath Ateeq Bassam SaleemAllah Almogadwy M.A.khan khan Muhammad Adnan Department of Computer Sciences Bahria University Lahore CampusLahore54000Pakistan Faculty of Information Technology Liwa CollegeAbu Dhabi20009UAE Department of Computing Skyline University CollegeSharjah999041UAE Department of Computer Science Taibah UniversityMedina42315Saudi Arabia Riphah School of Computing and Innovation Faculty of ComputingRiphah International UniversityLahore54000Pakistan Department of Software Faculty of Artificial Intelligence and SoftwareGachon UniversitySeongnam13120Korea

Cervical cancer is an intrusive cancer that imitates various women around the world. Cervical cancer ranks in thefourth position because of the leading death cause in its premature stages. The cervix which is the lower end of thevagina that connects the uterus and vagina forms a cancerous tumor very slowly. This pre-mature cancerous tumorin the cervix is deadly if it cannot be detected in the early stages. So, in this delineated study, the proposed approachuses federated machine learning with numerous machine learning solvers for the prediction of cervical cancer totrain the weights with varying neurons empowered fuzzed techniques to align the neurons, Internet of MedicalThings (IoMT) to fetch data and blockchain technology for data privacy and models protection from hazardousattacks. The proposed approach achieves the highest cervical cancer prediction accuracy of 99.26% and a 0.74%misprediction rate. So, the proposed approach shows the best prediction results of cervical cancer in its early stageswith the help of patient clinical records, and all medical professionals will get beneficial diagnosing approachesfrom this study and detect cervical cancer in its early stages which reduce the overall death ratio of women due tocervical cancer.

关键词： Cervical cancer federated machine learning neurons blockchain technology

Federated Machine Learning Based Fetal Health Prediction Empowered with Bio-Signal Cardiotocography

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Computers, Materials & Continua 2024年第3期78卷 3303-3321页

作者： Muhammad Umar Nasir Omar Kassem Khalil Karamath Ateeq Bassam SaleemAllah Almogadwy Muhammad Adnan khan Muhammad Hasnain Azam khan Muhammad Adnan Department of Computer Sciences Bahria University Lahore CampusLahore54000Pakistan Faculty of Information Technology Liwa CollegeAbu Dhabi00000United Arab Emirates Department of Computing Skyline University CollegeSharjah1797United Arab Emirates Department of Computer Science Taibah UniversityMedina42353Saudi Arabia Riphah School of Computing and Innovation Faculty of ComputingRiphah International UniversityLahore CampusLahore54000Pakistan Department of Engineering and Development Dubizzle LabsLahore54000Pakistan Department of Software Faculty of Artificial Intelligence and SoftwareGachon UniversitySeongnam-si13120Korea

Cardiotocography measures the fetal heart rate in the fetus during pregnancy to ensure physical health because cardiotocography gives data about fetal heart rate and uterine shrinkages which is very beneficial to detect whether the fetus is normal or suspect or *** cardiotocography measures infer wrongly and give wrong predictions because of human *** traditional way of reading the cardiotocography measures is the time taken and belongs to numerous human errors as *** condition is very important to measure at numerous stages and give proper medications to the fetus for its *** the current period Machine learning(ML)is a well-known classification strategy used in the biomedical field on various issues because ML is very fast and gives appropriate results that are better than traditional *** techniques play a pivotal role in detecting fetal disease in its early *** research article uses Federated machine learning(FML)and ML techniques to classify the condition of the *** study proposed a model for the detection of bio-signal cardiotocography that uses FML and ML techniques to train and test the ***,the proposed model of FML used numerous data preprocessing techniques to overcome data deficiency and achieves 99.06%and 0.94%of prediction accuracy and misprediction rate,respectively,and parallel the proposed model applying K-nearest neighbor(KNN)and achieves 82.93%and 17.07%of prediction accuracy and misprediction accuracy,***,by comparing both models FML outperformed the KNN technique and achieved the best and most appropriate prediction results as compared with previous studies the proposed study achieves the best and most accurate results.

关键词： Cardiotocography ML FML fetal disease bio-signal

National guidelines for the diagnosis and treatment of hilar cholangiocarcinoma

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World Journal of Gastroenterology 2024年第9期30卷 1018-1042页

作者： Faisal Saud Dar Zaigham Abbas Irfan Ahmed Muhammad Atique Usman Iqbal Aujla Muhammad Azeemuddin Zeba Aziz abu Bakar Hafeez Bhatti Tariq Ali Bangash Amna Subhan Butt Osama Tariq Butt Abdul Wahab Dogar Javed Iqbal Farooqi Faisal Hanif Jahanzaib Haider Siraj Haider Syed Mujahid Hassan Adnan Abdul Jabbar Aman Nawaz khan Muhammad Shoaib khan Muhammad Yasir khan Amer Latif Nasir Hassan Luck Ahmad Karim Malik Kamran Rashid Sohail Rashid Mohammad Salih Abdullah Saeed Amjad Salamat Ghias-un-Nabi Tayyab Aasim Yusuf Haseeb Haider Zia Ammara Naveed Department of Hepatopancreatic Biliary Surgery&Liver Transplant Pakistan Kidney and Liver Institute&Research CentreLahore 54000Pakistan Department of Hepatogastroenterology and Liver Transplantation Dr.Ziauddin University HospitalKarachi 75600SindhPakistan University of Aberdeen Aberdeen B243FXUnited Kingdom Department of Pathology Pakistan Kidney and Liver Institute&Research CentreLahore 54000Pakistan Department of Gastroenterology&Hepatology Pakistan Kidney and Liver Institute&Research CentreLahore 54000Pakistan Department of Radiology Aga Khan UniversityKarachi 74800Pakistan Department of Oncology Hameed Latif HospitalLahore 54000Pakistan Division of Hepatopancreatic Biliary Surgery&Liver Transplantation Shifa International HospitalIslamabad 44000Pakistan Department of Hepatopancreatic Biliary Surgery&Liver Transplant Shaikh Zayed Hospital and Post Graduate Medical InstituteLahore 54000Pakistan Department of Medicine Aga Khan University HospitalKarachi 74800Pakistan Department of Liver Transplant Pir Abdul Qadir Shah Jeelani Institute of Medical SciencesGambat 66020Pakistan Department of Medicine&Gastroenterology Lifecare Hospital and Research CentrePeshawar 25000Khyber PakhtunkhwaPakistan Department of Hepatopancreatobiliary&Liver Transplant Bahria International HospitalLahore 54000Pakistan Department of Surgery Hepatopancreatobiliary&Liver TransplantDow University of Health SciencesKarachi 74800Pakistan Department of Gastroenterology Hepatology&NutritionPir Abdul Qadir Shah Jeelani Institute of Medical SciencesGambat 66020Pakistan Department of Oncology Dr.Ziauddin HospitalKarachi 74800Pakistan Department of Radiology Rehman Medical InstitutePeshawar 25000Pakistan Army Liver Transplant Unit Pak Emirates Military HospitalRawalpindi 46000Pakistan Department of Gastroenterology Sindh Institute of Urology and TransplantationKarachi 75500Pakistan Rashid Nursing Home and Cancer Clinic Rashid Nursing Home and Cancer ClinicRawalpindi 46000Pakistan Department of Gastroentero

A consensus meeting of national experts from all major national hepatobiliary centres in the country was held on May 26,2023,at the Pakistan Kidney and Liver Institute&Research Centre(PKLI&RC)after initial consultations with the *** Pakistan Society for the Study of Liver Diseases(PSSLD)and PKLI&RC jointly organised this *** effort was based on a comprehensive literature review to establish national practice guidelines for hilar cholangiocarcinoma(hCCA).The consensus was that hCCA is a complex disease and requires a multidisciplinary team approach to best manage these *** coordinated effort can minimise delays and give patients a chance for curative treatment and effective *** diagnostic and staging workup includes high-quality computed tomography,magnetic resonance imaging,and magnetic resonance *** cytology or biopsy utilizing endoscopic retrograde cholangiopancreatography is a mainstay for ***,histopathologic confirmation is not always required before *** ultrasound with fine needle aspiration of regional lymph nodes and positron emission tomography scan are valuable adjuncts for *** only curative treatment is the surgical resection of the biliary tree based on the Bismuth-Corlette *** patients with unresectable hCCA can be considered for liver *** chemotherapy should be offered to patients with a high risk of *** use of preoperative biliary drainage and the need for portal vein embolisation should be based on local multidisciplinary *** with acute cholangitis can be drained with endoscopic or percutaneous biliary *** chemotherapy with cisplatin and gemcitabine has shown improved survival in patients with irresectable and recurrent hCCA.

关键词： Hilar cholangiocarcinoma Bismuth-Corlette classification Memorial Sloan Kettering Cancer Centre Staging Preoperative biliary drainage Portal vein embolisation Surgical resection Hepatectomy

Enhanced Steganalysis for Color Images Using Curvelet Features and Support Vector Machine

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Computers, Materials & Continua 2024年第1期78卷 1311-1328页

作者： Arslan Akram Imran khan Javed Rashid Mubbashar Saddique Muhammad Idrees Yazeed Yasin Ghadi Abdulmohsen Algarni Faculty of Computer Science and Information Technology Department of Computer ScienceSuperior UniversityLahore54000Pakistan Machine Learning Code(MLC)Lab Meharban HouseHouse Number 209Zafar ColonyOkara56300Pakistan Information Technology Services University of OkaraOkara56310Pakistan Department of Computer Science&Engineering University of Engineering&Technology LahoreNarowal CampusNarowal51601Pakistan Department of Computer Science and Software Engineering Al Ain UniversityAl Ain11671Abu Dhabi Department of Computer Science King Khalid UniversityAbha61421Saudi Arabia

Algorithms for steganography are methods of hiding data transfers in media *** machine learning architectures have been presented recently to improve stego image identification performance by using spatial information,and these methods have made it feasible to handle a wide range of problems associated with image *** with little information or low payload are used by information embedding methods,but the goal of all contemporary research is to employ high-payload images for *** address the need for both low-and high-payload images,this work provides a machine-learning approach to steganography image classification that uses Curvelet transformation to efficiently extract characteristics from both type of *** Vector Machine(SVM),a commonplace classification technique,has been employed to determine whether the image is a stego or *** Wavelet Obtained Weights(WOW),Spatial Universal Wavelet Relative Distortion(S-UNIWARD),Highly Undetectable Steganography(HUGO),and Minimizing the Power of Optimal Detector(MiPOD)steganography techniques are used in a variety of experimental scenarios to evaluate the performance of the *** WOW at several payloads,the proposed approach proves its classification accuracy of 98.60%.It exhibits its superiority over SOTA methods.

关键词： Curvelets fast fourier transformation support vector machine high pass filters steganography

Outpatient insulin use in type 2 diabetes mellitus and acute respiratory distress syndrome outcomes:A retrospective cohort study

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World Journal of Clinical Cases 2024年第17期12卷 2966-2975页

作者： Georges Khattar Samer Asmar Laurence Aoun Fares Saliba Shaza Almardini Saif abu Baker Catherine Hong Carolla El Chamieh Fadi Haddadin Toni Habib Omar Mourad Zeina Morcos Fatema Arafa Jonathan Mina Khalil El Gharib Mohammad Aldalahmeh Salman khan Elie Bou Sanayeh Department of Medicine Holy Spirit University of KaslikJounieh 00000Lebanon Department of Internal Medicine Staten Island University HospitalStaten IslandNY 10305United States Public Heath and Biostatistics Independent ResearchBeirut 0000Lebanon Department of Medicine Lebanese UniversityBeirut 00000Lebanon Department of Medicine University of BalamandBeirut 00000Lebanon Department of Medicine Lebanese American UniversityBeirut 00000Lebanon Department of Medicine Northwell Health Staten Island University HospitalNew YorkNY 10305United States

BACKGROUND The impact of type 2 diabetes mellitus(T2DM)on acute respiratory distress syndrome(ARDS)is debatable.T2DM was suspected to reduce the risk and complications of ***,during coronavirus disease 2019(COVID-19),T2DM predisposed patients to ARDS,especially those who were on insulin at *** evaluate the impact of outpatient insulin use in T2DM patients on non-COVID-19 ARDS *** We conducted a retrospective cohort analysis using the Nationwide Inpatient Sample *** patients diagnosed with ARDS were stratified into insulin-dependent diabetes mellitus(DM)(IDDM)and non-insulindependent DM(NIDDM)*** applying exclusion criteria and matching over 20 variables,we compared cohorts for mortality,duration of mechanical ventilation,incidence of acute kidney injury(AKI),length of stay(LOS),hospitalization costs,and other clinical *** Following 1:1 propensity score matching,the analysis included 274 patients in each ***,no statistically significant differences emerged between the IDDM and NIDDM groups in terms of mortality rates(32.8%vs 31.0%,P=0.520),median hospital LOS(10 d,P=0.537),requirement for mechanical ventilation,incidence rates of sepsis,pneumonia or AKI,median total hospitalization costs,or patient disposition upon *** Compared to alternative anti-diabetic medications,outpatient insulin treatment does not appear to exert an independent influence on in-hospital morbidity or mortality in diabetic patients with non-COVID-19 ARDS.

关键词： Acute respiratory distress syndrome Type 2 diabetes mellitus Insulin Length of stay Mortality Endotracheal intubation Acute kidney injury Coronavirus disease 2019

Enhancing Mild Cognitive Impairment Detection through Efficient Magnetic Resonance Image Analysis

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Computers, Materials & Continua 2024年第8期80卷 2081-2098页

作者： Atif Mehmood Zhonglong Zheng Rizwan khan Ahmad Al Smadi Farah Shahid Shahid Iqbal Mutasem K.Alsmadi Yazeed Yasin Ghadi Syed Aziz Shah Mostafa M.Ibrahim Department of Computer Science and Technology Zhejiang Normal UniversityJinhua321002China Zhejiang Institute of Photoelectronics&Zhejiang Institute for Advanced Light Source Zhejiang Normal UniversityJinhua321004China Department of Data Science and Artificial Intelligence Zarqa UniversityZarqa13100Jordan School of Chemical and Environmental Engineering College of ChemistryChemical Engineering andMaterials ScienceSoochow UniversitySuzhou215123China Department of Management Information Systems College of Applied Studies and Community ServiceImam Abdulrahman Bin Faisal UniversityDammam32244Saudi Arabia Department of Computer Science Al Ain UniversityAbu Dhabi999041United Arab Emirates Department of Electrical Engineering Faculty of EngineeringMinia UniversityMinia61519Egypt Healthcare Technology and Innovation Theme Faculty Research Centre for Intelligent HealthcareCoventry UniversityCoventryCV48BWUK

Neuroimaging has emerged over the last few decades as a crucial tool in diagnosing Alzheimer’s disease(AD).Mild cognitive impairment(MCI)is a condition that falls between the spectrum of normal cognitive function and ***,previous studies have mainly used handcrafted features to classify MCI,AD,and normal control(NC)*** paper focuses on using gray matter(GM)scans obtained through magnetic resonance imaging(MRI)for the diagnosis of individuals with MCI,AD,and *** improve classification performance,we developed two transfer learning strategies with data augmentation(i.e.,shear range,rotation,zoom range,channel shift).The first approach is a deep Siamese network(DSN),and the second approach involves using a cross-domain strategy with customized *** performed experiments on the Alzheimer’s Disease Neuroimaging Initiative(ADNI)dataset to evaluate the performance of our proposed *** experimental results demonstrate superior performance in classifying the three binary classification tasks:NC ***,NC ***,and MCI ***,we achieved a classification accuracy of 97.68%,94.25%,and 92.18%for the three cases,*** study proposes two transfer learning strategies with data augmentation to accurately diagnose MCI,AD,and normal control individuals using GM *** findings provide promising results for future research and clinical applications in the early detection and diagnosis of AD.

关键词： Alzheimer’s disease mild cognitive impairment normal control transfer learning classification augmentation

CNTFET Based Grounded Active Inductor for Broadband Applications

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Computers, Materials & Continua 2022年第10期73卷 2135-2149页

作者： Muhammad I.Masud Nasir Shaikh-Husin Iqbal A.khan abu K.Bin A’Ain Department of Electrical Engineering Umm Al Qura UniversityMakkah21955Saudi Arabia School of Electrical Engineering Faculty of EngineeringUniversiti Teknologi MalaysiaJohor Bahru81310JohorMalaysia

A new carbon nanotube field effect transistor(CNTFET)based grounded active inductor(GAI)circuit is presented in this *** suggested GAI offers a tunable inductance with a very wide inductive bandwidth,high quality factor(QF)and low power *** tunability of the realized circuit is achieved through CNTFET based *** proposed topology shows inductive behavior in the frequency range of 0.1–101 GHz and achieves to a maximum QF of *** GAI operates at 0.7 V with 0.337 mW of power *** demonstrate the performance of GAI,a broadband low noise amplifier(LNA)circuit is designed by utilizing the GAI based input *** realized LNA provides high frequency bandwidth(17.5–57 GHz),low noise figure(<3 dB)and occupies less space due to absence of any spiral ***,it exhibits a flat forward gain of 15.9 than±0.9 dB,a reverse isolation less than−63 dB and input return loss less−10 dB over the entire frequency *** proposed CNTFET based GAI and LNA circuits are designed and verified by using HSPICE simulations with Stanford CNTFET model at 16 nm technology node.

关键词： Active inductor gyrator-C CNTFET quality factor selfresonance frequency

Seasonal abundance and Diversity of Birds of Prey and Owls in Al Wathba Wetland Reserve in abu Dhabi, UAE

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Open Journal of Ecology 2024年第3期14卷 228-244页

作者： Shakeel Ahmed Salim Jáved Shahid B. khan Eissa Al Hammadi Abdullah Al Hammadi Nouf Sameer Alqadi Environment Agency-abu Dhabi Abu Dhabi United Arab Emirates

Inland wetlands in abu Dhabi Emirate are wintering and stopover sites for migratory birds of prey. We conducted long-term regular monitoring surveys in Al Wathba Wetland Reserve (AWWR) from January 1995 to December 2022. Both diurnal and occasionally nocturnal surveys were undertaken to record the migratory raptors and owls in the Wetland Reserve. During the study, a total of 1282 regular monitoring visits were undertaken and 27 species of diurnal raptors and owls representing five families and three orders were detected. These represent 57% of the total species of birds of prey recorded in the UAE. Overall, 63% of all the species that we observed were Accipitriformes followed by 26% Falconiformes and 11% Strigiformes. We found that changes in mean daily temperature have a positive effect on raptor species diversity and abundance in the Wetland Reserve. The species encounter rate was higher in low temperature as compared to high temperature and overall regression equation was statistically significant F (4, 1126) = 8.49), p = 0.00). However, the numbers of raptors did not vary significantly across the years (p = 0.51). Western Marsh-harrier (Circus aeruginosus) and Greater Spotted Eagle (Clanga clanga) were recorded to be the most abundant species in the wetland reserve followed by Common Kestrel (Falco tinnunculus). However, the encounter rate of globally threatened Greater Spotted Eagle was detected to have significantly decreased since 2016. Moreover, 63% of the species detected were uncommon and rarely recorded such as 1) Saker Falcon 2) Lanner Falcon 3) Long-eared Owl & Merlin, which were the rare records from the wetland reserve. Furthermore, 27 years of regular monitoring in the wetland have yielded diverse diurnal raptors and owl fauna (H) = 0.83, (E) = 1.43 (Shannon Diversity Index). The results demonstrate that long-term monitoring surveys in arid environments are essential to determine the trends in the raptor populations and to document rare and globally

关键词： Wetland Reserve Raptors abundance Diversity abu Dhabi Inland Wetland AWWR Greater Spotted Eagle

Milestones of Wireless Communication Networks and Technology Prospect of Next Generation(6G)

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Computers, Materials & Continua 2022年第6期71卷 4803-4818页

作者： Mohammed H.Alsharif Md.Sanwar Hossain abu Jahid Muhammad Asghar khan Bong Jun Choi Samih M.Mostafa Department of Electrical Engineering College of Electronics and Information EngineeringSejong University209 Neungdong-roGwangjin-guSeoul05006Korea Department of Electrical and Electronic Engineering Bangladesh University of Business and TechnologyDhaka1216Bangladesh Department of Electrical&Computer Engineering University of OttawaOttawaON K1N 6N5Canada Department of Electrical Engineering Hamdard University KarachiIslamabad CampusIslamabad44000Pakistan School of Computer Science and Engineering&School of Electronic Engineering Soongsil UniversitySeoulKorea Faculty of Computers and Information South Valley UniversityQena83523Egypt Academy of Scientific Research and Technology Cairo11516Egypt

Since around 1980,a new generation of wireless technology has arisen approximately every 10 ***-generation(1G)and secondgeneration(2G)began with voice and eventually introduced more and more data in third-generation(3G)and became highly popular in the fourthgeneration(4G).To increase the data rate along with low latency and mass connectivity the fifth-generation(5G)networks are being installed from ***,the 5G technology will not be able to fulfill the data demand at the end of this ***,it is expected that 6G communication networks will rise,providing better services through the implementation of new enabling technologies and allowing users to connect everywhere.6G technology would not be confined to cellular communications networks,but would also comply with non-terrestrial communication system requirements,such as satellite *** ultimate objectives of this work are to address the major challenges of the evolution of cellular communication networks and to discourse the recent growth of the industry based on the key scopes of application and *** main areas of research topics are summarized into(i)major 6G wireless networkmilestones;(ii)key performance indicators;(iii)future new applications;and(iv)potential fields of research,challenges,and open issues.

关键词： Wireless networks beyond 5G 6G communications terahertz frequency terahertz communications holographic calls