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Antibacterial conductive self-healing hydrogel wound dressing with dual dynamic bonds promotes infected wound healing

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Bioactive Materials 2023年第12期30卷 129-141页

作者： Lipeng Qiao Yongping Liang Jueying Chen Ying Huang Saeed A.Alsareii abdulrahman manaa alamri Farid A.Harraz Baolin Guo Key Laboratory of Shaanxi Province for Craniofacial Precision Medicine Research College of StomatologyXi’an Jiaotong UniversityXi’an710049China Frontier Institute of Science and Technology State Key Laboratory for Mechanical Behavior of MaterialsXi’an Jiaotong UniversityXi’an710049China Department of Surgery College of MedicineNajran UniversityNajran11001Saudi Arabia Promising Centre for Sensors and Electronic Devices(PCSED) Advanced Materials and Nano-Research CentreNajran UniversityNajran11001Saudi Arabia Department of Orthopaedics The First Affiliated Hospital of Xi’an Jiaotong UniversityXi’an710061China

In clinical applications,there is a lack of wound dressings that combine efficient resistance to drug-resistant bacteria with good self-healing *** this study,a series of adhesive self-healing conductive antibacterial hydrogel dressings based on oxidized sodium alginate-grafted dopamine/carboxymethyl chitosan/Fe3+(OSD/CMC/Fe hydrogel)/polydopamine-encapsulated poly(thiophene-3-acetic acid)(OSD/CMC/Fe/PA hydrogel)were prepared for the repair of infected *** Schiff base and Fe3+coordination bonds of the hydrogel structure are dynamic bonds that can be repaired automatically after the hydrogel network is ***,the hydrogel exhibits self-healing properties,allowing the hydrogel dressing to adapt to complex wound *** OSD/CMC/Fe/PA hydrogel showed good conductivity and photothermal antibacterial properties under near-infrared(NIR)light *** addition,the hydrogels exhibit tunable rheological properties,suitable mechanical properties,antioxidant properties,tissue adhesion properties and hemostatic ***,all hydrogel dressings improved wound healing in the infected full-thickness defect skin wound repair test in *** wound size repaired by OSD/CMC/Fe/PA3 hydrogel+NIR was much smaller(12%)than the control group treated with Tegaderm™film after 14 *** conclusion,the hydrogels have high antibacterial efficiency,suitable conductivity,great self-healing properties,good biocompatibility,hemostasis and antioxidant properties,making them promising candidates for wound healing dressings for the treatment of infected skin wounds.

关键词： Dynamic crosslinking Self-healing Infected wound Photothermal antibacterial Wound healing

Breast Cancer Detection in Saudi Arabian Women Using Hybrid Machine Learning on Mammographic Images

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Computers, Materials & Continua 2022年第9期72卷 4833-4851页

作者： Yassir Edrees Almalki Ahmad Shaf Tariq Ali Muhammad Aamir Sharifa Khalid Alduraibi Shoayea Mohessen Almutiri Muhammad Irfan Mohammad Abd Alkhalik Basha Alaa Khalid Alduraibi abdulrahman manaa alamri Muhammad Zeeshan Azam Khalaf Alshamrani Hassan A.Alshamrani Division of Radiology Department of MedicineMedical CollegeNajran UniversityNajran61441Kingdom of Saudi Arabia Department of Computer Science COMSATS University IslamabadSahiwal CampusSahiwal57000Pakistan Department of Radiology College of MedicineQassim UniversityBuraidah52571Kingdom of Saudi Arabia Department of Radiology King Fahad Specialist HospitalBuraydah52571Kingdom of Saudi Arabia Electrical Engineering Department College of EngineeringNajran UniversityNajran61441Kingdom of Saudi Arabia Radiology Department Human Medicine CollegeZagazig UniversityZagazig44631Egypt Department of Surgery College of MedicineNajran UniversityNajran61441Kingdom of Saudi Arabia Department of Computer Science Bahauddin Zakariya UniversityMultan66000Pakistan Radiological Sciences Department College of Applied Medical SciencesNajran UniversityNajran61441Kingdom of Saudi Arabia

Breast cancer(BC)is the most common cause of women’s deaths *** mammography technique is the most important modality for the detection of *** detect abnormalities in mammographic images,the Breast Imaging Reporting and Data System(BI-RADs)is used as a *** correct allocation of BI-RADs categories for mammographic images is always an interesting task,even for *** this work,to detect and classify the mammogram images in BI-RADs,a novel hybrid model is presented using a convolutional neural network(CNN)with the integration of a support vector machine(SVM).The dataset used in this research was collected from different hospitals in the Qassim health cluster of Saudi *** collection of all categories of BI-RADs is one of the major contributions of this *** significant contribution is the development of a hybrid approach through the integration of CNN and *** proposed hybrid approach uses three CNN models to obtain ensemble CNN model *** ensemble model saves the values to integrate them with *** proposed system achieved a classification accuracy,sensitivity,specificity,precision,and F1-score of 93.6%,94.8%,96.9%,96.6%,and 95.7%,*** proposed model achieved better performance compared to previously available methods.

关键词： Breast cancer CNN SVM BIRADS classification

LBP–Bilateral Based Feature Fusion for Breast Cancer Diagnosis

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Computers, Materials & Continua 2022年第11期73卷 4103-4121页

作者： Yassir Edrees Almalki Maida Khalid Sharifa Khalid Alduraibi Qudsia Yousaf Maryam Zaffar Shoayea Mohessen Almutiri Muhammad Irfan Mohammad Abd Alkhalik Basha Alaa Khalid Alduraibi abdulrahman manaa alamri Khalaf Alshamrani Hassan A.Alshamrani Division of Radiology Department of MedicineMedical CollegeNajran UniversityNajran 61441Saudi Arabia Department of Computer Science and Information Technology Ibadat International UniversityIslamabad44000Pakistan Department of Radiology College of MedicineQassim UniversityBuraidah 52571Saudi Arabia Department of Radiology King Fahad Specialist HospitalBuraydah 52571Saudi Arabia Electrical Engineering Department College of EngineeringNajran UniversityNajran 61441Saudi Arabia Radiology Department Human Medicine CollegeZagazig UniversityZagazig 44631Egypt Department of Surgery College of MedicineNajran UniversityNajran 61441Saudi Arabia Radiological Sciences Department College of Applied Medical SciencesNajran UniversityNajran 61441Saudi Arabia

Since reporting cases of breast cancer are on the rise all over the *** in regions such as Pakistan,Saudi Arabia,and the United *** methods for the early detection and diagnosis of breast cancer are *** usual diagnosis procedures followed by physicians has been updated with modern diagnostic approaches that include computer-aided support for better *** learning based practices has increased the accuracy and efficiency of medical diagnosis,which has helped save lives of many *** is much research in the field of medical imaging diagnostics that can be applied to the variety of data such as magnetic resonance images(MRIs),mammograms,X-rays,ultrasounds,and histopathological images,but magnetic resonance(MR)and mammogram imaging have proved to present the promising *** proposed paper has presented the results of classification algorithms over Breast Cancer(BC)mammograms from a novel dataset taken from hospitals in the Qassim health cluster of Saudi *** paper has developed a novel approach called the novel spectral extraction algorithm(NSEA)that uses feature extraction and fusion by using local binary pattern(LBP)and bilateral algorithms,as well as a support vector machine(SVM)as a *** NSEA with the SVM classifier demonstrated a promising accuracy of 94%and an elapsed time of 0.68 milliseconds,which were significantly better results than those of comparative experiments from classifiers named Naïve Bayes,logistic regression,K-Nearest Neighbor(KNN),Gaussian Discriminant Analysis(GDA),AdaBoost and Extreme Learning Machine(ELM).ELM produced the comparative accuracy of 94%however has a lower elapsed time of 1.35 as compared to *** has produced a fairly well accuracy of 82%,KNN has a low accuracy of 66%.However Logistic Regression,GDA and Naïve Bayes have produced the lowest accuracies of 47%,43%and 42%.

关键词： Artificial intelligence machine learning breast cancer mammograms supervised learning classification feature fusion

Machine-Learning-Enabled Obesity Level Prediction Through Electronic Health Records

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Computer Systems Science & Engineering 2023年第9期46卷 3715-3728页

作者： Saeed Ali Alsareii Muhammad Awais abdulrahman manaa alamri Mansour Yousef AlAsmari Muhammad Irfan Mohsin Raza Umer Manzoor Department of Surgery College of MedicineNajran UniversityNajran61441Saudi Arabia Department of Computer Science Edge Hill UniversitySt Helens RdOrmskirkL394QPUK Electrical Engineering Department College of EngineeringNajran UniversityNajran61441Saudi Arabia Department of Computer Science Aston UniversityBirminghamB47ETUK

Obesity is a critical health condition that severely affects an individual’s quality of life *** occurrence of obesity is strongly associated with extreme health conditions,such as cardiac diseases,diabetes,hypertension,and some types of ***,it is vital to avoid obesity and or reverse its *** healthy food habits and an active lifestyle can help to prevent *** this regard,artificial intelligence(AI)can play an important role in estimating health conditions and detecting obesity and its *** study aims to see obesity levels in adults by implementing AIenabled machine learning on a real-life *** dataset is in the form of electronic health records(EHR)containing data on several aspects of daily living,such as dietary habits,physical conditions,and lifestyle variables for various participants with different health conditions(underweight,normal,overweight,and obesity type I,II and III),expressed in terms of a variety of features or parameters,such as physical condition,food intake,lifestyle and mode of *** classifiers,i.e.,eXtreme gradient boosting classifier(XGB),support vector machine(SVM),and artificial neural network(ANN),are implemented to detect the status of several conditions,including obesity *** findings indicate that the proposed XGB-based system outperforms the existing obesity level estimation methods,achieving overall performance rates of 98.5%and 99.6%in the scenarios explored.

关键词： Artificial intelligence obesity machine learning extreme gradient boosting classifier support vector machine artificial neural network electronic health records physical activity obesity levels

Injury Pattern among Road Traffic Accidents’ Victims in Najran City, Saudi Arabia

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International Journal of Clinical Medicine 2018年第4期9卷 270-280页

作者： Mahdi Yahya Al-Zamanan Abdullah Saleh Al-Yami Ali Abdullah Al-Najrani Mansour Yousef Al-Asmari abdulrahman alamri manaa Awad Mohammed Al-Qahtani Mohammed Helmy Faris Shalayel Abdulhadi Mohamed Elbashir Saeed Ali Alsareii College of Medicine Najran University Najran Saudi Arabia Department of Surgery College of Medicine Najran University Najran Saudi Arabia Department of Surgery College of Medicine Najran University Najran Saudi Arabia Department of Family and Community Medicine College of Medicine Najran University Najran Saudi Arabia

Traffic accidents constitute the substantial cause of disability and mortality in the young Saudi individuals reaching horrible figures. The aim of this study was to review and identify the pattern of injury among road traffic accident (RTA) victims as well as the peak time of accidents and their implications. This retrospective hospital-based cross-sectional study was carried out in the period between April 2016 to March 2017 in King Khalid Hospital, Maternity and Children Hospital and Najran General Hospital, Najran, Saudi Arabia. All RTA victims admitted to the emergency departments of the pre-mentioned hospitals. Data collected from 435 Saudis and non-Saudis’ files were statistically analyzed with regard to age, gender, the timing of road traffic accidents, injury pattern, and neurological deficits incidence. Most of the RTAs’ cases (92%) were male victims with the highest peak in the age group 20 - 29 years. 58% of the RTAs happened in the evening (6:00 PM-9:00 PM) while 20% occurred in the morning. Head injury represented the most frequent pattern (36%) followed by the spinal injury (23%), lower limb injury (23%), upper limb injury (20%), thoracic injury (17%), pelvic injury and abdominal injury (8%). 4.4% of RTAs resulted in death whilst 9% of cases experienced neurological deficits. In conclusion, young male drivers in Najran recorded the highest frequency of RTAs. Initiation of road safety education and expansion of speed detectors (Saher) system deployment is highly recommended.

关键词： Road Traffic Accidents (RTA) Road Traffic Injuries (RTIs) Disability

Epidemiological Pattern of Breast Diseases among Females in the South-Western Region, Saudi Arabia

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International Journal of Clinical Medicine 2020年第5期11卷 257-269页

作者： abdulrahman manaa alamri Saeed Ali Alsareii Hajr Al-Wadei Awad Mohammed Al-Qahtani Salem Ali Alatef Sultan Sara Ali Alshamrani Ahmed Hamzah Almakrami Abdullah Ahmed Daiel Ahlam Yahya Alyami Ashwaq Mousa Hommadi Yagoub Mohammed Tahir Ali Department of Surgery College of Medicine Najran University Najran KSA Department of Community Medicine Faculty of Medicine Najran University Najran KSA College of Medicine Najran University Najran KSA Department of General surgery King Khalid Hospital Najran KSA

Background: Breast diseases cover several conditions. The majority of breast diseases are noncancerous. Some of these lesions are clinically unremarkable, which needed minimal intervention. However, some symptoms may be of clinical value and attract the attention of both the patient and the attending physician, especially when they become persistent. The study aimed to assess the prevalence, pattern, types, and clinical profile of breast diseases among females in the South-western region, during the period from 2018-2020. Methods: A retrospective record-based descriptive approach was used through reviewing medical records of all cases with breast disease attended King Khalid Hospital during the period from January 2018 to January 2020. Data extracted throng pre-structured questionnaire. Results: The study included 211 cases whose ages ranged from 18 to 58 years old with a mean age of 28.9 ± 12.8 years. Breast mass was the most recorded complaint (95.1%) followed with breast pain (32%), skin changes. Benign findings based on the final pathology report were recorded for more than two thirds of the cases, with the most common finding were fibroadenoma. Excisional biopsy and modified radical mastectomy were the most reported surgical interventions. Conclusions: In conclusion, the study revealed that the majority of the cases had benign breast disease (BBD), where fibroadenoma was the most frequent.

关键词： Breast Disease Females Incidence Pattern Predictors Epidemiolo-gylesions Biopsy

Densely Convolutional BU-NET Framework for Breast Multi-Organ Cancer Nuclei Segmentation through Histopathological Slides and Classification Using Optimized Features

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Computer Modeling in Engineering & Sciences 2024年第12期141卷 2375-2397页

作者： Amjad Rehman Muhammad Mujahid Robertas Damasevicius Faten S.alamri Tanzila Saba Artificial Intelligence&Data Analytics Lab College of Computer&Information Sciences(CCIS)Prince Sultan UniversityRiyadh11586Saudi Arabia Centre of Real Time Computer Systems Kaunas University of TechnologyKaunasLT-51386Lithuania Department of Mathematical Sciences College of SciencePrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia

This study aims to develop a computational pathology approach that can properly detect and distinguish histology *** is crucial for histopathological image analysis,as it involves segmenting cell ***,challenges exist,such as determining the boundary region of normal and deformed nuclei and identifying small,irregular nuclei *** learning approaches are currently dominant in digital pathology for nucleus recognition and classification,but their complex features limit their practical use in clinical *** existing studies have limited accuracy,significant processing costs,and a lack of resilience and generalizability across diverse *** proposed the densely convolutional Breast U-shaped Network(BU-NET)framework to overcome the mentioned *** study employs BU-NET’s spatial and channel attention methods to enhance segmentation *** inclusion of residual blocks and skip connections in the BU-NEt architecture enhances the process of extracting features and reconstructing the *** enhances the robustness of training and convergence processes by reducing the occurrence of vanishing *** primary objective of BU-NEt is to enhance the model’s capacity to acquire and analyze more intricate features,all the while preserving an efficient working *** BU-NET experiments demonstrate that the framework achieved 88.7%average accuracy,88.8%F1 score for Multi-Organ Nuclei Segmentation Challenge(MoNuSeg),and 91.2%average accuracy,91.8%average F1 for the triple-negative breast cancer(TNBC)*** framework also achieved 93.92 Area under the ROC Curve(AUC)for *** results demonstrated that the technology surpasses existing techniques in terms of accuracy and effectiveness in ***,it showcases the ability to withstand and recover from different tissue types and diseases,indicating possible uses in medical *** research evaluated the efficacy of the proposed method

关键词： Breast cancer histopathology BU-NET deep learning

Biochemical and radiological predictors of malignant biliary strictures

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World Journal of Gastroenterology 2004年第10期10卷 1504-1507页

作者： Ibrahim A.AI-Mofleh abdulrahman M.Aljebreen Saleh M.alamri Rashed S.AJ-Rashed Faleh Z.Al-Faleh Hussein M.AJ-Freihi Ayman A.Abdo Arthur C.Isnani Gastroenterology Division department of Medicine (38)King Khalid University HospitalRiyadhKingdom of Saudi Arabia King Khalid University Hospital College of Medicine and Research Center (74)PO Box 2925Riyadh 11461Kingdom of Saudi Arabia

AIM: Differentiation of benign biliary strictures (BBS) from malignant biliary strictures (MBS) remains difficult despite improvement in imaging and endoscopic techniques. The aim of this study was to identify the clinical, biochemical and or radiological predictors of malignant biliary ***: We retrospectively reviewed all charts of patients who had biliary strictures (BS) on endoscopic retrograde cholangiopancreatography (ERCP) or percutaneous cholangiography (PTC) in case of unsuccessful ERCP from March 1998 to August 2002. Patient characteristics, clinical features, biochemical, radiological and biopsy results were all recorded. Stricture etiology was determined based on cytology,biopsy or clinical follow-up. A receiver operator characteristic (ROC) curve was constructed to determine the optimal laboratory diagnostic criterion threshold in predicting ***: One hundred twenty six patients with biliary strictures were enrolled, of which 72 were malignant. The mean age for BBS was 53 years compared to 62.4 years for MBS (P=0.0006). Distal bile duct stricture was mainly due to a malignant process 48.6% vs 9% (P=0.001). Alkaline phosphates and AST levels were more significantly elevated in MBS (P=0.0002). ROC curve showed that a bilirubin level of 84 μmol/L or more was the most predictive of MBS with a sensitivity of 98.6%, specificity of 59.3% and a positive likelihood ratio of 2.42 (95% CI=0.649-0.810). Proximal biliary dilatation was more frequently encountered in MBS compared to BBS, 73.8% vs39.5% (P=0.0001). Majority of BBS (87%) and MBS (78%) were managed ***: A serum bilirubin level of 84 μmol/L or greater is the best predictor of MBS. Older age, proximal biliary dilatation, higher levels of bilirubin, alkaline phosphatase, ALT and AST are all associated with MBS. ERCP is necessary to diagnose and treat benign and malignant biliary strictures.

关键词： Biliary Tract Diseases Biliary Tract Neoplasms Constriction, Pathologic Predictive Value of Tests Age Factors Bilirubin Cholangiography Cholangiopancreatography, Endoscopic Retrograde Humans Middle Aged ROC Curve Retrospective Studies Sensitivity and Specificity

Blockchain-Based Decentralized Authentication Model for IoT-Based E-Learning and Educational Environments

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Computers, Materials & Continua 2023年第5期75卷 3133-3158页

作者： Osama A.Khashan Sultan alamri Waleed Alomoush Mutasem K.Alsmadi Samer Atawneh Usama Mir Research and Innovation Centers Rabdan AcademyP.O.Box 114646Abu DhabiUnited Arab Emirates College of Computing and Informatics Saudi Electronic UniversityRiyadh13316Saudi Arabia School of Information Technology Skyline University CollegeP.O.Box 1797SharjahUnited Arab Emirates Department of MIS College of Applied Studies and Community ServicesImam Abdulrahman Bin Faisal UniversityP.O.Box 1982DammamSaudi Arabia Department of Computer Science University of WindsorWindsorN9J3Y1Canada

In recent times,technology has advanced significantly and is currently being integrated into educational environments to facilitate distance learning and interaction between *** the Internet of Things(IoT)into education can facilitate the teaching and learning process and expand the context in which students ***,learning data is very sensitive and must be protected when transmitted over the network or stored in data ***,the identity and the authenticity of interacting students,instructors,and staff need to be verified to mitigate the impact of ***,most of the current security and authentication schemes are centralized,relying on trusted third-party cloud servers,to facilitate continuous secure *** addition,most of these schemes are resourceintensive;thus,security and efficiency issues arise when heterogeneous and resource-limited IoT devices are being *** this paper,we propose a blockchain-based architecture that accurately identifies and authenticates learners and their IoT devices in a decentralized manner and prevents the unauthorized modification of stored learning records in a distributed university *** allows students and instructors to easily migrate to and join multiple universities within the network using their identity without the need for user *** proposed architecture was tested using a simulation tool,and measured to evaluate its *** simulation results demonstrate the ability of the proposed architecture to significantly increase the throughput of learning transactions(40%),reduce the communication overhead and response time(26%),improve authentication efficiency(27%),and reduce the IoT power consumption(35%)compared to the centralized authentication *** addition,the security analysis proves the effectiveness of the proposed architecture in resisting various attacks and ensuring the security requirements of learning data in the unive

关键词： Blockchain decentralized authentication Internet of Things(IoT) E-learning IoT security