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World Journal of Clinical Cases 2023年第6期11卷 1310-1317页

作者： Bassant S Moussa Zeinab M Abd Elatiff Ghada M Kamal Eldin Elhadary Emergency Medicine Department Suez Canal UniversityFaculty of MedicineIsmailia 41522Egypt

BACKGROUND Disorders of consciousness including coma in non-trauma patients can be caused by a wide variety of pathologies affecting the central nervous system.They represent a frequent challenge in emergency medicine and are combined with a very high in-hospital mortality.Hence,early treatment of these patients is vital and increases the likelihood of a good outcome.AIM To identify the causes of altered consciousness presentation to the Emergency Department at suez Canal university Hospital.METHODS This was a descriptive cross-sectional study conducted on 87 patients with acute non-traumatic disturbed level of consciousness(DLOC)at the Emergency Department.RESULTS The mean age of the studied patients was 60.5±13.6 years.Among them,60%were males and 40%were females.The most common cause of acute non-traumatic DLOC was systemic infection,such as sepsis and septic shock(25.3%),followed by respiratory causes(24.1%)and neurological causes(18.4%).CONCLUSION The most common cause of acute non-traumatic DLOC was systemic infections followed by respiratory and neurological causes.

关键词： Disturbed level of consciousness Non-traumatic Emergency department

Shear Let Transform Residual Learning Approach for Single-Image Super-Resolution

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Computers, Materials & Continua 2024年第5期79卷 3193-3209页

作者： Israa Ismail Ghada Eltaweel Mohamed Meselhy Eltoukhy Department of Computer Science Faculty of Computers and InformaticsSuez Canal UniversityIsmailia51422Egypt Department of Information Technology College of Computing and Information Technology at KhulaisUniversity of JeddahJeddahSaudi Arabia

Super-resolution techniques are employed to enhance image resolution by reconstructing high-resolution images from one or more low-resolution inputs.Super-resolution is of paramount importance in the context of remote sensing,satellite,aerial,security and surveillance imaging.Super-resolution remote sensing imagery is essential for surveillance and security purposes,enabling authorities to monitor remote or sensitive areas with greater clarity.This study introduces a single-image super-resolution approach for remote sensing images,utilizing deep shearlet residual learning in the shearlet transform domain,and incorporating the Enhanced Deep Super-Resolution network(EDSR).Unlike conventional approaches that estimate residuals between high and low-resolution images,the proposed approach calculates the shearlet coefficients for the desired high-resolution image using the provided low-resolution image instead of estimating a residual image between the high-and low-resolution image.The shearlet transform is chosen for its excellent sparse approximation capabilities.Initially,remote sensing images are transformed into the shearlet domain,which divides the input image into low and high frequencies.The shearlet coefficients are fed into the EDSR network.The high-resolution image is subsequently reconstructed using the inverse shearlet transform.The incorporation of the EDSR network enhances training stability,leading to improved generated images.The experimental results from the Deep Shearlet Residual Learning approach demonstrate its superior performance in remote sensing image recovery,effectively restoring both global topology and local edge detail information,thereby enhancing image quality.Compared to other networks,our proposed approach outperforms the state-of-the-art in terms of image quality,achieving an average peak signal-to-noise ratio of 35 and a structural similarity index measure of approximately 0.9.

关键词： Super-resolution shearlet transform shearlet coefficients enhanced deep super-resolution network

Mafic and felsic magmatism in the Wadi Kalalat area, South Eastern Desert, Egypt: mineralogy, geochemistry and geodynamic evolution during the Neoproterozoic in the Nubian Shield

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Acta Geochimica 2024年第1期43卷 150-173页

作者： Adel A.Surour Ahmed A.Madani Mohamed A.El-Sobky Faculty of Science Galala UniversityNew Galala CitySuez 43511Egypt Department of Geology Faculty of ScienceCairo UniversityGiza 12613Egypt Egyptian Mineral Resources Authority P.O.Box 11517AbbasiyaCairoEgypt

In the south Eastern Desert of Egypt,two contrasting types of magmatism(mafic and felsic) are recorded in the Wadi Kalalat area,and form the Gabal El Motaghiarat and Gabal Batuga intrusions,respectively.The two intrusions post-dates ophiolitic and arc associations represented by serpentinite and metagabbro-diorite,respectively.The mafic intrusion has a basal ultramafic member represented by fresh peridotite,which is followed upward by olivine gabbro and anorthositic or leucogabbro.This mafic intrusion pertains to the Alaskan-type mafic-ultramafic intrusions in the Arabian-Nubian Shield(ANS)being of tholeiitic nature and emplaced in a typical arc setting.On the other hand,the Gabal Batuga intrusion comprises three varieties of fresh A-type granites of high K-calc alkaline nature,which is peraluminous and garnetbearing in parts.A narrow thermal aureole in the olivine gabbro of the mafic intrusion was developed due to the intrusion of the Batuga granites.This results in the development of a hornfelsic melagabbro variety in which the composition changed from tholeiitic to a calc-alkaline composition due to the addition of S_(i)O_(2),Al_(2)O_(3),alkalis,lithosphile elements(LILEs) such as Rb(70 ppm) and Y(28 ppm) from the felsic intrusion.Outside the thermal aureole,Rb amounts 2-8 ppm and Y lies in the range <2-6ppm.It is believed that the Gabal Batuga felsic intrusion started to emplace during the waning stage of an arc system,with transition from the pre-collisional(i.e.,arc setting) to post-collisional and within plate settings.Magma from which the Gabal Batuga granites were fractionated is high-K calc-alkaline giving rise to a typical post-collisional A-type granite(A_(2)-subtype) indicating an origin from an underplating crustal source.Accordingly,it is stressed here that the younger granites in the ANS are not exclusively post-collisional and within-plate but most likely they started to develop before closure of the arc system.The possible source(s) of mafic magmas that resulted in the formation of the two intru

关键词： Wadi Kalalat Gabal El Motaghairat mafic intrusion Gabal Batuga felsic intrusion Arc setting Post-collision Within-plate

Particle Swarm Optimization-Based Hyperparameters Tuning of Machine Learning Models for Big COVID-19 Data Analysis

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Journal of Computer and Communications 2024年第3期12卷 160-183页

作者： Hend S. Salem Mohamed A. Mead Ghada S. El-Taweel Department of Computer Sciences Suez Canal University Ismailia Egypt

Analyzing big data, especially medical data, helps to provide good health care to patients and face the risks of death. The COVID-19 pandemic has had a significant impact on public health worldwide, emphasizing the need for effective risk prediction models. Machine learning (ML) techniques have shown promise in analyzing complex data patterns and predicting disease outcomes. The accuracy of these techniques is greatly affected by changing their parameters. Hyperparameter optimization plays a crucial role in improving model performance. In this work, the Particle Swarm Optimization (PSO) algorithm was used to effectively search the hyperparameter space and improve the predictive power of the machine learning models by identifying the optimal hyperparameters that can provide the highest accuracy. A dataset with a variety of clinical and epidemiological characteristics linked to COVID-19 cases was used in this study. Various machine learning models, including Random Forests, Decision Trees, Support Vector Machines, and Neural Networks, were utilized to capture the complex relationships present in the data. To evaluate the predictive performance of the models, the accuracy metric was employed. The experimental findings showed that the suggested method of estimating COVID-19 risk is effective. When compared to baseline models, the optimized machine learning models performed better and produced better results.

关键词： Big COVID-19 Data Machine Learning Hyperparameter Optimization Particle Swarm Optimization Computational Intelligence

The Prevalence of Irritable Bowel Syndrome among Medical and Non-Medical suez Canal university Students

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Open Journal of Gastroenterology 2015年第5期5卷 42-48页

作者： Mariam M. Darweesh Mennat Allah M. Abd El Hameed Yomna M. Hassan Khadiga A. Abd El Rheem Shaza A. Mohamed Marwa A. Mahdy Ahmed A. Slwawy Mona M. Abo El Ftooh Faculty of Medicine Suez Canal University Ismailia Egypt

Background: Irritable bowel syndrome (IBS) is one of the most frequently diagnosed gastrointestinal (GI) disorders in primary care and gastroenterology practices, despite the fact that many suffer symptoms without knowing their diagnosis or seek for medical consult, so this study aims to explore the prevalence of irritable bowel syndrome (IBS) among suez Canal university students. Methods: A cross section. With multistage cluster probability sample. Using Rome criteria III IBS module, the questionnaire was administrated to suez Canal university students;a population consisting of (86) students of the faculty of medicine & non-medical (84) students of the faculty of commerce English section with total (170) students of the third batch from both faculties (whose mean age is 20 ± 0.82) years old with total (109) females and (61) males. Results: The prevalence of IBS according to Rome III criteria in suez Canal university was 22.9%. 23.8% were diseased in the faculty of commerce while 22.1% in faculty of medicine. Females in this study represent 64.1% of the sample, 30.3% of them were diseased, while males represent 35.9% about 9.8% of them were diseased. IBS constipation predominant type was 28.2%, diarrhea predominant type was 15.4%, mixed type was 46.2%, the unsubtyped cases represent 10.3%. Conclusion: Irritable bowel syndrome is a common disease among suez Canal university students, more common in non medical students than medical ones, can be considered as a female predominant disease. And this requires a real medical concern.

关键词： Prevalence Irritable Bowel Syndrome IBS Gastrointestinal Diseases Rome III Criteria

Assessment of Physicians’ Knowledge, Attitude and Practices of Radiation Safety at suez Canal university Hospital, Egypt

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Open Journal of Radiology 2015年第4期5卷 250-258页

作者： Rasha F. Abdellah Shaimaa A. Attia Ahmed M. Fouad Amani W. Abdel-Halim Community Medicine Department Faculty of Medicine Suez Canal University Ismailia Egypt

Doctors who request imaging must be well trained in deciding whether diagnostic imaging is indicated and have an accurate knowledge of the associated risks. Although radiological doses are low and the chance of late effect is minimal, it should be kept as low as reasonably achievable. This cannot be achieved without a proper knowledge and adherence to safe practices. This cross-sectional study investigates the level of physicians’ knowledge about radiation safety and their attitude towards radiation protection. A self-administered questionnaire, for radiation safety was sent to a purposive sample of 120 physicians at suez Canal university Hospital. Eighty questionnaires were filled by participants (response rate;66.7%). The sample included 22 radiologists, 15 oncologists, 25 surgeons and 18 orthopedists. Most participants did not receive any radiation safety-related training (88.8%). Radiologists and oncologists were exposed to ionizing radiation more frequently;however, their knowledge was as low as that of other physicians. The overall knowledge score ranged from 40% - 60% (mean;56.5 ± 15.2), with a low score among surgeons and orthopedics. The most deficient knowledge was in the dose of background radiation and the radiation dose received by patients in each type of radiation procedure. Adherence to safe radiation practices was violated by most of participants, especially surgeons and orthopedics, but they attributed it to the poor applicability of the protective measures during performing the procedures. This study concluded that physicians at the suez Canal university Hospital had deficient knowledge, unsafe practices and negative attitude towards radiation safety policies & precautions.

关键词： Physicians’ Knowledge Attitude Practice Radiation Safety

Robust Machine Learning Technique to Classify COVID-19 Using Fusion of Texture and Vesselness of X-Ray Images

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Computer Modeling in Engineering & Sciences 2024年第2期138卷 1981-2004页

作者： Shaik Mahaboob Basha Victor Hugo Cde Albuquerque Samia Allaoua Chelloug Mohamed Abd Elaziz Shaik Hashmitha Mohisin Suhail Parvaze Pathan Department of Electronics and Communication Engineering N.B.K.R.Institute of Science&TechnologyVidyanagarAndhra Pradesh524413India Department of Teleinformatics Engineering Federal University of CearáFortaleza60455-970Brazil Information Technology Department College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh84428Saudi Arabia Department of Mathematics Faculty of ScienceZagazig UniversityZagazig44519Egypt Faculty of Computer Science and Engineering Galala UniversitySuez435611Egypt Artificial Intelligence Research Center(AIRC) College of Engineering and Information TechnologyAjman UniversityAjmanUnited Arab Emirates Department of Electrical and Computer Engineering Lebanese American UniversityByblos13-5053Lebanon Department of Avionics Indian Institute of Space Science and TechnologyThiruvananthapuramKerala695547India Department of Veterinary Clinical Sciences University of MinnesotaSt.PaulMinnesota55108USA

Manual investigation of chest radiography(CXR)images by physicians is crucial for effective decision-making in COVID-19 diagnosis.However,the high demand during the pandemic necessitates auxiliary help through image analysis and machine learning techniques.This study presents a multi-threshold-based segmentation technique to probe high pixel intensity regions in CXR images of various pathologies,including normal cases.Texture information is extracted using gray co-occurrence matrix(GLCM)-based features,while vessel-like features are obtained using Frangi,Sato,and Meijering filters.Machine learning models employing Decision Tree(DT)and RandomForest(RF)approaches are designed to categorize CXR images into common lung infections,lung opacity(LO),COVID-19,and viral pneumonia(VP).The results demonstrate that the fusion of texture and vesselbased features provides an effective ML model for aiding diagnosis.The ML model validation using performance measures,including an accuracy of approximately 91.8%with an RF-based classifier,supports the usefulness of the feature set and classifier model in categorizing the four different pathologies.Furthermore,the study investigates the importance of the devised features in identifying the underlying pathology and incorporates histogrambased analysis.This analysis reveals varying natural pixel distributions in CXR images belonging to the normal,COVID-19,LO,and VP groups,motivating the incorporation of additional features such as mean,standard deviation,skewness,and percentile based on the filtered images.Notably,the study achieves a considerable improvement in categorizing COVID-19 from LO,with a true positive rate of 97%,further substantiating the effectiveness of the methodology implemented.

关键词： Chest radiography(CXR)image COVID-19 classifier machine learning random forest texture analysis

Infectious causes of fever of unknown origin in developing countries: An international ID-IRI study

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Journal of Intensive Medicine 2024年第1期4卷 94-100页

作者： Hakan Erdem Jaffar AAl-Tawfiq Maha Abid Wissal Ben Yahia George Akafity Manar Ezzelarab Ramadan Fatma Amer Amani El-Kholy Atousa Hakamifard Bilal Ahmad Rahimi Farouq Dayyab Hulya Caskurlu Reham Khedr Muhammad Tahir Lysien Zambrano Mumtaz Ali Khan Aun Raza Nagwa Mostafa El-Sayed Magdalena Baymakova Aysun Yalci Yasemin Cag Umran Elbahr Aamer Ikram Department of Infectious Diseases&Clinical Microbiology Gulhane School of MedicineTurkish Health Sciences UniversityAnkaraTurkey Specialty Internal Medicine and Quality and Patient Safety Department Johns Hopkins Aramco HealthcareDhahranSaudi Arabia Division of Infectious Diseases Indiana University School of MedicineIndianapolisINUSA Department of Infectious Diseases Farhat Hached University HospitalIbn El Jazzar Medical SchoolUniversity of SousseSousseTunisia Internal Medicine Department Farhat Hached University HospitalIbn El Jazzar Medical SchoolUniversity of SousseSousseTunisia Cape Coast Teaching Hospital Cape CoastGhana Medical Parasitology Faculty of MedicineSuez UniversitySuezEgypt Department of Medical Microbiology and Immunology Faculty of MedicineZagazig UniversityZagazigEgypt Department of Clinical Pathology Faculty of MedicineCairo UniversityGizaEgypt Department of Infectious Diseases School of MedicineIsfahan University of Medical SciencesIsfahanIran Department of Infectious Diseases Kandahar University Medical FacultyTeaching HospitalKandaharAfghanistan Department of Infectious Diseases Mohammed Bn Khalifa Bn Salman Alkhalifa Specialist Cardiac CenterAwaliBahrain Department of Infectious Diseases and Clinical Microbiology Faculty of MedicineIstanbul Medeniyet UniversityIstanbulTurkey Department of Pediatric Oncology National Cancer Institute–Cairo UniversityChildren Cancer Hospital EgyptCairoEgypt Department of Medicine Federal General HospitalIslamabadPakistan Institute for Research in Medical Sciences and Right to Health(ICIMEDES) Scientific Research Unit(UIC)Faculty of Medical Sciences(FCM)National Autonomous University of Honduras(UNAH)TegucigalpaHonduras National Institute of Health IslamabadPakistan Shaukat Khanum Memorial Cancer Hospital and Research Center LahorePakistan Medical Parasitology Department Research Institute of OphthalmologyGizaEgypt Department of Infectious Diseases Military Medical AcademySofiaBulgaria Department of Infecti

Background:Fever of unknown origin(FUO)in developing countries is an important dilemma and further research is needed to elucidate the infectious causes of FUO.Methods:A multi-center study for infectious causes of FUO in lower middle-income countries(LMIC)and lowincome countries(LIC)was conducted between January 1,2018 and January 1,2023.In total,15 participating centers from seven different countries provided the data,which were collected through the Infectious DiseasesInternational Research Initiative platform.Only adult patients with confirmed infection as the cause of FUO were included in the study.The severity parameters were quick Sequential Organ Failure Assessment(qSOFA)≥2,intensive care unit(ICU)admission,vasopressor use,and invasive mechanical ventilation(IMV).Results:A total of 160 patients with infectious FUO were included in the study.Overall,148(92.5%)patients had community-acquired infections and 12(7.5%)had hospital-acquired infections.The most common infectious syndromes were tuberculosis(TB)(n=27,16.9%),infective endocarditis(n=25,15.6%),malaria(n=21,13.1%),brucellosis(n=15,9.4%),and typhoid fever(n=9,5.6%).Plasmodium falciparum,Mycobacterium tuberculosis,Brucellae,Staphylococcus aureus,Salmonella typhi,and Rickettsiae were the leading infectious agents in this study.A total of 56(35.0%)cases had invasive procedures for diagnosis.The mean qSOFA score was 0.76±0.94{median(interquartile range[IQR]):0(0–1)}.ICU admission(n=26,16.2%),vasopressor use(n=14,8.8%),and IMV(n=10,6.3%)were not rare.Overall,38(23.8%)patients had at least one of the severity parameters.The mortality rate was 15(9.4%),and the mortality was attributable to the infection causing FUO in 12(7.5%)patients.Conclusions:In LMIC and LIC,tuberculosis and cardiac infections were the most severe and the leading infections causing FUO.

关键词： Developing countries Fever of unknown origin Infection

Assessment of the patients’outcomes after implementation of South African triage scale in emergency department,Egypt

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Chinese Journal of Traumatology 2022年第2期25卷 95-101页

作者： Adel Hamed Elbaih Ghada Kamal Elhadary Magda Ramdan Elbahrawy Samar Sami Saleh Emergency Medicine Department Faculty of MedicineSuez Canal UniversityIsmailiaEgypt

Purpose:Overcrowding in emergency department(ED)is a concerning global problem and has been identified as a national crisis in some countries.Several emergency sorting systems designed successfully in the world.Launched in 2004,a group of branches in South African triage scale(SATS)developed.The effectiveness of the case sorting system of SATS was evaluated to reduce the patient's length of stay(LOS)and mortality rate within the ED at suez Canal university Hospital.Methods:The study was designed as an intervention study that included a systematic random sample of patients who presented to the ED in suez Canal university Hospital.This study was implemented in three phases:pre-intervention phase,115 patients were assessed by the traditional protocols;intervention phase,a structured training program was provided to the ED staff,including a workshop and lectures;and post-intervention phase,230 patients were assessed by SATS.All the patients were retriaged 2 h later,calculating the LOS per patient and the mortality.Data was collected and entered using Microsoft Excel software.Collected data from the triage sheet were analyzed using the SPSS software program version 22.0.Results:The LOS in the ED was about 183.78 min before the intervention;while after the training program and the application of SATS,it was reduced to 51.39 min.About 15.7%of the patients died before the intervention;however,after the intervention the ratio decreased to 10.7%deaths.Conclusion:SATS is better at assessing patients without missing important data.Additionally,it resulted in a decrease in the LOS and reduction in the mortality rate compared to the traditional protocol.

关键词： Emergency service Triage Length of stay Mortality South African triage score

Adaptive Density-Based Spatial Clustering of Applications with Noise(ADBSCAN)for Clusters of Different Densities

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Computers, Materials & Continua 2023年第5期75卷 3695-3712页

作者： Ahmed Fahim Computer Science Department Prince Sattam bin Abdulaziz UniversityAflajSaudi Arabia Computer Science Department Faculty of Computers and InformationSuez UniversitySuezEgypt

Finding clusters based on density represents a significant class of clustering algorithms.These methods can discover clusters of various shapes and sizes.The most studied algorithm in this class is theDensity-Based Spatial Clustering of Applications with Noise(DBSCAN).It identifies clusters by grouping the densely connected objects into one group and discarding the noise objects.It requires two input parameters:epsilon(fixed neighborhood radius)and MinPts(the lowest number of objects in epsilon).However,it can’t handle clusters of various densities since it uses a global value for epsilon.This article proposes an adaptation of the DBSCAN method so it can discover clusters of varied densities besides reducing the required number of input parameters to only one.Only user input in the proposed method is the MinPts.Epsilon on the other hand,is computed automatically based on statistical information of the dataset.The proposed method finds the core distance for each object in the dataset,takes the average of these distances as the first value of epsilon,and finds the clusters satisfying this density level.The remaining unclustered objects will be clustered using a new value of epsilon that equals the average core distances of unclustered objects.This process continues until all objects have been clustered or the remaining unclustered objects are less than 0.006 of the dataset’s size.The proposed method requires MinPts only as an input parameter because epsilon is computed from data.Benchmark datasets were used to evaluate the effectiveness of the proposed method that produced promising results.Practical experiments demonstrate that the outstanding ability of the proposed method to detect clusters of different densities even if there is no separation between them.The accuracy of the method ranges from 92%to 100%for the experimented datasets.

关键词： Adaptive DBSCAN(ADBSCAN) Density-based clustering Data clustering Varied density clusters