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Open Journal of Radiology 2015年第3期5卷 125-130页

作者： Sami Nasreldein Abdelwally Eljak Caroline Edward Ayad elsafi ahmed abdalla Radiology Department Asser Central Hospital Saudi Arabia Saudi College of Medical Radiological Science Sudan University of Science and Technology Khartoum Sudan

Assessment of entrance skin doses for patients in Digital radiography examinations should be made as a means for the optimization of the radiation protection of the patients. We measured the entrance skin dose (ESD) received by 50 pediatrics undergoing 12 types of diagnostic X-ray examination at Radiology Department of Asser Central Hospital-KSA. The entrance skin dose ESD was determined via measurements parameters: focus to skin distance (FSD), tube current (mAs) and tube voltage (kV) in arithmetical equation. The mean ± SD for ESDs were found to be 0.16 ± 0.03, 0.21 ± 0.01, 0.63 ± 0.26, 0.55 ± 0.09, 0.15 ± 0.05, 0.27 ± 0.06, 0.41 ± 0.19, 0.46 ± 0.18, 0.46 ± 0.12, 0.20 ± 0.02, 0.39 ± 0.01, 0.29 ± 0.03, for PA chest, foot, AP pelvis, PA skull, PA hand, AP arm, ankle, AP shoulder, abdomen, forearm, AP femur, AP elbow consequently. Our study is considered as an attempt to evaluate the ESDs received by digital radiographic x-ray machine for children aged between 2 - 15 years old, taking in our considerations number of other variables. The mean ESD values obtained are found to be within the standard reference. The data obtained may add to the available information in national records for general use. It may provide guidance on where efforts on dose reduction will need to be directed to fulfill the requirements of the optimization process and serve as a reference for future researches.

关键词： Entrance Skin Dose Pediatrics Digital Radiography

New Sudanese Reference Chart of Fetal Bi-ometry and Weight Using Ultrasonography

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Open Journal of Radiology 2016年第2期6卷 131-139页

作者： Caroline Edward Ayad ahmed Abdelrahim Mohammed Ibrahim Mohammed Elfadil Mohammed GarElnabi Bushra Hussein ahmed elsafi ahmed abdalla Mohammed ahmed Elshiekh Saleem College of Medical Radiological Science Sudan University of Science and Technology Khartoum Sudan Faculty of Radiology Science and Medical Imaging Alzaiem Alazhari University Khartoum Sudan College of Medical Radiological Science and Nuclear Medicine The National Rabat University Khartoum Sudan

Background: Many centers in Sudan use the reference data for fetal biometry. The recently published population-based reference either overestimated or underestimated the weight of the fetuses. Objective: To establish a national reference for fetal biometry, and weight by gestational age for singleton fetuses in Sudan. Methods: Data were collected on all singleton live births documented in the data collection sheet done at Saudi Hospital from 2015 to 2016 (n = 225). Gestational age estimation was based on the last menstrual period and fetal ultrasound thereafter. Fetal biometry and weight and other 6 fetal weight formulae were assessed. Reference data for fetal growth by gestational age were created. Results: New charts and reference equations are reported in Sudanese population for fetal biparietal diameter, head circumference, abdominal circumference and femur length and fetal weight. Conclusion: We advocate that these reference charts and equations for fetal biometry and weight might be valuable in the clinical use for appropriate ethnic Sudanese.

关键词： Fetal Biometry Fetal Weight Gestational Age Ultrasonography

Assessment of Used Formulae for Sonographic Estimation of Fetal Weight in Sudanese Population

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Open Journal of Radiology 2016年第2期6卷 113-120页

作者： Caroline Edward Ayad ahmed Abdelrahim Mohammed Ibrahim Mohamed Elfadil Mohamed Garelnabi Bushra Hussein ahmed elsafi ahmed abdalla Mohammed ahmed Elshiekh Saleem College of Medical Radiological Science Sudan University of Science and Technology Khartoum Sudan Faculty of Radiology Science and Medical Imaging Alzaiem Alazhari University Khartoum Sudan College of Medical Radiological Science and Nuclear Medicine The National Rabat University Khartoum Sudan

The objective of this study is to assess commonly used formulae (Sheppard, Campbell, Hadlock I, II, III, and IV) for estimation of fetal weight in Sudanese population. A descriptive cross-sectional study was conducted at Saudi Hospital-Khartoum-Sudan;from December 2015 to April 2016. The study included 225 singleton pregnancies. The fetal biometry—Biparietal diameter (BPD), head circumference (HC), abdominal circumference (AC), femur length (FL) and actual birth weights (ABW) were taken. Statistical analysis showed significant results at p ≤ 0.005. Results showed that the significant highest positive correlation between the ABW and the EFW/Kg was seen in the Hadlock I, III and IV equations having an equal values (0.951) followed by Hadlock II (0.946), Sheppard (0.872) and lastly Campbell (-0.925) with significant high degree of negative correlation. The new established equation EFWFLHCAC is the best formula identified in our study to predict Sudanese babies weight ranged between 1.86 Kg to 3.987 Kg.

关键词： Ultrasonography Fetal Weight Gestational Age

Long-term outcomes of titanium-nitride-oxide coated stents and drug-eluting stents in acute coronary syndrome:A systematic review and meta-analysis

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World Journal of Cardiology 2024年第5期16卷 293-305页

作者： Muhammad ahmed Ali Fahim Afia Salman Hira Anas Khan Syed Muhammad Hasan Muskan FatimaBhojani Sarah Aslam Amna Zia Ul Haq Vishal Reddy Bejugam Beena Muntaha Nasir Wajiha Gul Abdul Moeed Abdelrahman S abdalla Muhammad Majid Muhammad Sohaib Asghar Md Al Hasibuzzaman Department of Internal Medicine Dow University of Health SciencesKarachi 74200Pakistan Department of Internal Medicine North Central Bronx HospitalBronxNY 10467United States Department of Urology Center for Academic MedicineStanford University School of MedicinePalo AltoCA 33872United States Department of Cardiovascular Imaging Cleveland ClinicClevelandOH 44195United States Division of Nephrology and Hypertension Mayo Clinic RochesterRochesterMN 55905United States Institute of Nutrition and Food Science University of DhakaDhaka 1000Bangladesh

BACKGROUND In severe cases of coronary artery disease,percutaneous coronary intervention provide promising *** stent used could be a drug-eluting stent(DES)or a titanium-nitride-oxide coated stent(TiNOS).AIM To compare the 5-year effectiveness and safety of the two stent *** The following systematic review and meta-analysis was conducted in accordance with the preferred reporting items for systematic reviews and meta-analysis guidelines,and PubMed/MEDLINE,Scopus,and Cochrane Central were searched from inception till August *** outcomes were major adverse cardiac events(MACE),cardiac death,myocardial infarction(MI),cardiac death or MI,and ischemia-driven total lesion revascularization(ID-TLR).RESULTS Four randomized controlled trials(RCT),which analyzed a sum total of 3045 patients with acute coronary syndrome(ACS)after a median follow-up time of 5 years were *** statistically insignificant,an increase in the ID-TLR was observed in patients receiving TiNOSs vs *** addition,MI,cardiac death and MI,and definite stent thrombosis(DST)were significantly decreased in the TiNOS *** analysis revealed no significant results with meta-regression presenting non-ST elevated MI(NSTEMI)as a statistically significant covariate in the outcome of *** TiNOS was found to be superior to DES in terms of MI,cardiac death or MI,and DST outcomes,however,the effect of the two stent types on ID-TLR and MACE was not significant.A greater number of studies are required to establish an accurate comparison of patient outcomes in TiNOS and DES.

关键词： Stents Drug-eluting Major adverse cardiac events All-cause death Meta-analysis

Effect of Diabetes Self-Management Education on Glycaemic Control in Sudanese Adults with Type 2 Diabetes

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Journal of Biosciences and Medicines 2024年第3期12卷 316-327页

作者： Sahar Moawia Balla Elnour Tayseer Abdelmotalib ahmed Taha Haiam abdalla Wadatalla Ziryab Zainelabdin Mohamed Elmahdi Marwah Isam Abdulmajeed Mohammedahmed Rowa Abdelmonem Sidig Hamadto Nahla Yousif Osman Mohammed Saeed Omnia Mubarak Saad abdallah Sulafa Abdelbagi Mustafa ahmed Hanady Abdelhameed ahmed Mohamed Sarah Khalil Fathi Khalil Family Medicine Health Gates Primary Care Riyadh SAU Family Medicine Dhaman Health Assurance Hospitals Company Kuwait KWT Family Medicine First Health Cluster Riyadh SAU Emergency Department Sheikh Khalifa Medical City Abudahbi ARE Family Medicine University of Medical Sciences and Technology Khartoum SDN Family Medicine Sudan Medical Specialization Board-Sudan Khartoum SDN Family Medicine Ultra Care Home Care Company Riyadh SAU Medicine Department Health Gates Primary Care Riyadh SAU Family Medicine Mouwasat Hospital Madinah SAU

Research Background: The high prevalence of diabetes in Sudan, estimated at 16%, highlights the importance of effective health education in diabetes management. Diabetes self-management education has been identified as a crucial tool in enhancing the knowledge, attitudes, and abilities necessary for self-management among individuals with diabetes. Aim: To assess the impact of diabetes self-management education on medication adherence and glycemic control in Sudanese adults with type 2 diabetes before and 3 months after the DSME intervention. Method: The study was conducted in Sudan between September 2022 and March 2023, it was an interventional, one-group, pre- and post-test study that aimed to assess the impact of diabetes self-management education (DSME) on medication adherence and diabetes control in Sudanese adults with type 2 diabetes. The research was conducted in primary health care centers in six cities in Sudan and involved 244 participants. The data entry and statistical analysis were conducted using the Statistical Package for Social Sciences version 27.0. A paired t test was used for analysis. Results: The study included 244 participants, 67% of whom were males. The age mean ± SD was 48.6 ± 9.3 years, and 85.3% of participants were married. Age at onset of diabetes mean ± SD was 40.60 ± 7.81 years;44.6% had diabetes for less than 5 years;and 84.1% had a positive family history of diabetes mellitus. The levels of poor, low, and partial adherence to medication decreased by 8.2%, 4%, and 20.6%, respectively, after the intervention. The levels of good and high medication regime adherence increased by 13% and 19.8%, respectively;BMI decreased by 1.1 ± 0.73 kg/m2 (p = 0.005). The fasting blood sugar decreased by 69 ± 32.9 mg/dl (p = 0.049), and the glycated hemoglobin decreased by 1.21 ± 0.28% (p = 0.001). Conclusions: The findings of this study reinforce the importance of patient education in improving glycemic control and enhancing self-management

关键词： Sudan Adherence Intervention Education Self-Management Diabetes

Parkinson’s Detection Using RNN-Graph-LSTM with Optimization Based on Speech Signals

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Computers, Materials & Continua 2022年第7期72卷 871-886页

作者： ahmed S.Almasoud Taiseer abdalla Elfadil Eisa Fahd N.Al-Wesabi Abubakar elsafi Mesfer Al Duhayyim Ishfaq Yaseen Manar ahmed Hamza Abdelwahed Motwakel Department of Information Systems College of Computer and Information SciencesPrince Sultan UniversityMahayil62529Saudi Arabia Department of Information Systems-Girls Section King Khalid UniversityMahayil62529Saudi Arabia Department of Computer Science College of Science and Artsat MahayilKing Khalid UniversityMahayil62529Saudi Arabia Faculty of Computer and IT Sana’a UniversitySana’aYemen Department of Software Engineering College of Computer Science and EngineeringUniversity of JeddahSaudi Arabia Department of Natural and Applied Sciences College of Community-AflajPrince Sattam bin Abdulaziz UniversityMahayil62529Saudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharj62529Saudi Arabia

Early detection of Parkinson’s Disease(PD)using the PD patients’voice changes would avoid the intervention before the identification of physical *** machine learning algorithms were developed to detect PD ***,these ML methods are lack in generalization and reduced classification performance due to subject *** overcome these issues,this proposed work apply graph long short term memory(GLSTM)model to classify the dynamic features of the PD patient speech *** proposed classification model has been further improved by implementing the recurrent neural network(RNN)in batch normalization layer of GLSTM and optimized with adaptive moment estimation(ADAM)on network hidden *** consider the importance of feature engineering,this proposed system use Linear Discriminant analysis(LDA)for dimensionality reduction and SparseAuto-Encoder(SAE)for extracting the dynamic speech *** on the computation of energy content transited from unvoiced to voice(onset)and voice to voiceless(offset),dynamic features are *** PD datasets is evaluated under 10 fold cross validation without sample *** proposed smart PD detection method called RNN-GLSTM-ADAM is numerically experimented with persistent phonations in terms of accuracy,sensitivity,and specificity andMatthew correlation *** evaluated result of RNN-GLSTM-ADAM extremely improves the PD detection accuracy than static feature based conventional ML and DL approaches.

关键词： Dimensionality reduction LDA feature extraction auto encoder classification recurrent neural network LSTM and optimization

Sports Prediction Model through Cloud Computing and Big Data Based on Artificial Intelligence Method

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Journal of Intelligent Learning Systems and Applications 2024年第2期16卷 53-79页

作者： Aws I. Abu Eid Achraf Ben Miled Ahlem Fatnassi Majid A. Nawaz Ashraf F. A. Mahmoud Faroug A. abdalla Chams Jabnoun Aida Dhibi Firas M. Allan Mohammed ahmed Elhossiny Salem Belhaj Imen Ben Mohamed Faculty of Computing Studies Arab Open University Amman Jordan Computer Science Department Science College Northern Border University Arar Kingdom of Saudi Arabia Artificial Intelligence and Data Engineering Laboratory LR21ES23 Faculty of Sciences of Bizerte University of Carthage Tunis Tunisia Applied College Northern Border University Arar Kingdom of Saudi Arabia Faculty of Specific Education Mansoura University Mansoura Egypt

This article delves into the intricate relationship between big data, cloud computing, and artificial intelligence, shedding light on their fundamental attributes and interdependence. It explores the seamless amalgamation of AI methodologies within cloud computing and big data analytics, encompassing the development of a cloud computing framework built on the robust foundation of the Hadoop platform, enriched by AI learning algorithms. Additionally, it examines the creation of a predictive model empowered by tailored artificial intelligence techniques. Rigorous simulations are conducted to extract valuable insights, facilitating method evaluation and performance assessment, all within the dynamic Hadoop environment, thereby reaffirming the precision of the proposed approach. The results and analysis section reveals compelling findings derived from comprehensive simulations within the Hadoop environment. These outcomes demonstrate the efficacy of the Sport AI Model (SAIM) framework in enhancing the accuracy of sports-related outcome predictions. Through meticulous mathematical analyses and performance assessments, integrating AI with big data emerges as a powerful tool for optimizing decision-making in sports. The discussion section extends the implications of these results, highlighting the potential for SAIM to revolutionize sports forecasting, strategic planning, and performance optimization for players and coaches. The combination of big data, cloud computing, and AI offers a promising avenue for future advancements in sports analytics. This research underscores the synergy between these technologies and paves the way for innovative approaches to sports-related decision-making and performance enhancement.

关键词： Artificial Intelligence Machine Learning Spark Apache Big Data SAIM

Aspartate transferase-to-platelet ratio index-plus: A new simplified model for predicting the risk of mortality among patients with COVID-19

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World Journal of Gastroenterology 2022年第16期28卷 1671-1680页

作者： Ali Madian ahmed Eliwa Hytham abdalla Haitham A Azeem Aly Department of Internal Medicine Faculty of MedicineAl-Azhar University-AssiutAssiut 71524Egypt Department of Internal Medicine Faculty of MedicineAl-Azhar University-CairoCairo 11754Egypt Department of Chest Diseases Faculty of MedicineAl-Azhar University-AssiutAssiut 71524Egypt

BACKGROUND Coronavirus disease 2019(COVID-19)has a spectrum of clinical syndromes with serious involvement of the lung and frequent effection of the liver and hemostatic *** biomarkers are affordable,rapid,objective,and useful in the evaluation and prognostication of COVID-19 *** To investigate the association between aspartate transferase-to-platelet ratio index(APRI)and in-hospital mortality to develop a COVID-19 mortality prediction *** A multicenter cohort study with a retrospective design was *** records of all consecutive adult patients admitted to Al-Azhar University Hospital(Assiut,Egypt)and Chest Hospital(Assiut,Egypt)with confirmed COVID-19 from July 1,2020 to October 1,2020,were retrieved and *** patient cohort was classified into the following two categories based on the APRI:(1)COVID-19 presenting with APRI≤0.5;and(2)COVID-19 presenting with APRI(>0.5 and≤1.5).The association between APRI and all-cause in-hospital mortality was analyzed,and the new model was developed through logistic regression *** Of the 353 patients who satisfied the inclusion criteria,10%were admitted to the intensive care unit(n=36)and 7%died during the hospital stay(n=25).The median age was 40 years and 50.7%were *** admission,49%had aspartate transferase-dominant liver *** admission,APRI(>0.5 and≤1.5)was independently associated with all-cause in-hospital mortality in unadjusted regression analysis and after adjustment for age and sex;after stepwise adjustment for several clinically relevant confounders,APRI was still significantly associated with all-cause inhospital *** admission,APRI(>0.5 and≤1.5)increased the odds of mortality by fivetimes(P<0.006).From these results,we developed a new predictive model,the APRI-plus,which includes the four predictors of age,aspartate transferase,platelets,and serum *** for mortality was very good,with an area under the receiver operating curve

关键词： COVID-19 Aspartate transferase-to-platelet ratio index Aspartate transferase All-cause inhospital mortality Serum ferritin SARS-CoV-2

Prediction of fold-of-increase in productivity index post limited entry fracturing using artificial neural network

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Petroleum Research 2022年第2期7卷 236-245页

作者： Shady Galal Ramah Mohamed abdalla Othman ahmed Z.Nouh Tarek El-Kwidy Faculty of Petroleum Engineering Suez UniversityEgypt Qarun Petroleum Company Egypt Egyptian Petroleum Research Institute Egypt American University in Cairo Egypt

Unified Fracture Design(UFD)bridges the gap between practices and theory in the hydraulic fracturing *** represents a technique to design hydraulic fracturing treatment with a particular amount of *** design could provide the maximum fold-of-increase(FOI)in productivity-index(PI)after hydraulic fracturing *** UFD optimization tool is very effective,but it has assumptions like any other *** assumption of UFD optimization technique;is a single-layer *** assumption does not align with the limited entry fracturing design *** limited entry fracturing,the frictional pressure is employed to offset the stress differences between multi-layers reservoirs to attain fluid injection through these layers,intended to deliver an optimal fracture conductivity in all *** drawback of this assumption is the underestimation of the actual value of FOI in *** paper aims to recast the original unified fracture design approach to extend the optimal UFD to a multilayer reservoir to predict the FOI in PI after limited entry fracturing *** recasting tool for this problem to find the optimum solution is Artificial Neural Networks(ANN).The architected ANN model is based on actual historical data of limited entry fracturing treatments.A statistical comparison between the proposed ANN model and classical UFD technique demonstrates that ANN model solution has a more reliable estimation of FOI in PI with the actual historical data.

关键词： Unified fracture design Hydraulic fracturing Limited-entry Fold of increase Artificial neural networks

Integration of Fog Computing for Health Record Management Using Blockchain Technology

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Computers, Materials & Continua 2022年第5期71卷 4135-4149页

作者： Mesfer AI Duhayyim Fahd N.Al-Wesabi Radwa Marzouk abdalla Ibrahim abdalla Musa Noha Negm Anwer Mustafa Hilal Manar ahmed Hamza Mohammed Rizwanullah Department of Natural and Applied Sciences College of Community AflajPrince Sattam Bin Abdulaziz UniversitySaudi Arabia Department of Computer Science College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia&Faculty of Computer and ITSana’a UniversityYemen Department of Information Systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversitySaudi Arabia&Department of MathematicsFaculty of ScienceCairo UniversityGiza12613Egypt Department of Computer Science College of ComputerQassim UniversityBuraydahSaudi Arabia Department of Computer Science King Khaled UniversityKSA&Faculty of ScienceDepartment of Mathematics and Computer ScienceMenoufia UniversityEgypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam Bin Abdulaziz UniversityAlKharjSaudi Arabia

Internet of Medical Things (IoMT) is a breakthrough technologyin the transfer of medical data via a communication system. Wearable sensordevices collect patient data and transfer them through mobile internet, thatis, the IoMT. Recently, the shift in paradigm from manual data storage toelectronic health recording on fog, edge, and cloud computing has been *** advanced computing technologies have facilitated medical services withminimum cost and available conditions. However, the IoMT raises a highconcern on network security and patient data privacy in the health caresystem. The main issue is the transmission of health data with high security inthe fog computing model. In today’s market, the best solution is blockchaintechnology. This technology provides high-end security and authenticationin storing and transferring data. In this research, a blockchain-based fogcomputing model is proposed for the IoMT. The proposed technique embedsa block chain with the yet another consensus (YAC) protocol building securityinfrastructure into fog computing for storing and transferring IoMT data inthe network. YAC is a consensus protocol that authenticates the input datain the block chain. In this scenario, the patients and their family membersare allowed to access the data. The empirical outcome of the proposedtechnique indicates high reliability and security against dangerous *** major advantages of using the blockchain model are high transparency,good traceability, and high processing speed. The technique also exhibitshigh reliability and efficiency in accessing data with secure transmission. Theproposed technique achieves 95% reliability in transferring a large number offiles up to 10,000.

关键词： Fog computing IoMT block chain YAC security IoT consensus protocol