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| 1 | Mortality and rebleeding following variceal haemorrhage in liver cirrhosis and periportal fibrosis显示文摘AIM To investigate mortality and rebleeding rate and identify associated risk factors at 6 wk and 5 d following acute variceal haemorrhage in patients with liver cirrhosis and schistosomal periportal fibrosis.METHODS This is a prospective study conducted during the period from March to December 2014. Patients with portal hypertension presenting with acute variceal haemorrhage secondary to either liver cirrhosis(group A) or schistosomal periportal fibroses(group B) presenting within 24 h of the onset of the bleeding were enrolled in the study and followed for a period of 6 wk. Analysis of data was done by Microsoft Excel and comparison between groups was done by Statistical Package of Social Sciences version 20 to calculate means and find the levels of statistical differences and define the mortality rates, the P value of < 0.05 was considered to be significant. RESULTS A total of 94 patients were enrolled in the study. Thirtytwo patients(34%) had liver cirrhosis(group A) and62(66%) patients had periportal fibrosis(group B).Mortality: The 6-wk and 5-d mortality were 53% and16% respectively in group A compared to 10% and 0%in group B(P value < 0.000 and < 0.004). In group A;a Child-Turcotte-Pugh class C and rebleeding within 5 d were significantly associated with 5-d mortality(P value< 0.029 and < 0.049 respectively) and Child- TurcottePugh class C was also a significant risk factor for 6-wk mortality(P value < 0.018). In group B; mortality was significantly associated with rebleeding within the 6-wk follow-up period and requirement for blood transfusion on admission(P value < 0.005 and < 0.049). Rebleeding:The 6-wk and 5-d rebleeding rate in group A were 56%and 25% respectively compared to 32% and 3% in group B(P value < 0.015 and < 0.002). Clinical presentation with encephalopathy was a significant risk factor for 5 d rebleeding in group A(P value < 0.005) while grade Ⅲperiportal fibrosis and requirement for blood transfusion on admission were significant risk factors for 6-wk rebleeding in group B(P value < 0.004 and < 0.02).CONCLUSION The 6-wk and 5-d mortality and rebleeding rate were significantly higher in patients with liver cirrhosis compared to patients with schistosomal periportal fibrosis. | Sara Elfadil Abbas Mohammed Abdelmunem Eltayeb Abdo Hatim Mohamed Yousif Mudawi | 2016 | World Journal of Hepatology2016，8，31： | 3 |
| 2 | Endovenous therapy of varicose veins : a better outcome than standard surgery? 显示文摘 | Samaraee A McCallum I J Mudawi A | 2009 | Sur- geon2009，7，3： | 1 |
| 3 | Selective site right ventricular pacing显示文摘 | Albouaini K Alkrmi A Mudawi T | 2009 | Heart2009，95，24： | 1 |
| 4 | Endovenous therapyof varicose veins:a better outcome than standard surgery?显示文摘 | AI Samaraee A McCallum IJ Mudawi A | 2009 | Surgeon2009，7，3： | 1 |
| 5 | Outcome of 'Kissing Stents' for Aortoiliac Atherosclerotic Disease, Including the Effect on the Non-diseased Contralateral Iliac Limb显示文摘 | Faheez Mohamed B. Sarkar G. Timmons A. Mudawi H. Ashour R. Uberoi | 2002 | CardioVascular and Interventional Radiology2002，，6： | 1 |
| 6 | Endovenous thera- py of varicose veins:a better outcome than standard surgery?显示文摘 | AI Samaraee A McCallum IJ Mudawi A | 2009 | Surgeon2009，7，3： | 1 |
| 7 | Selective site right ventrieular pacing 显示文摘 | Albouaini K Alkarmi A Mudawi T | 2009 | Heart2009，95，24： | 1 |
| 8 | Selective site right ventricular pacing显示文摘 | Albouaini K Alkarmi A Mudawi T | 2009 | Heart2009，95，24： | 1 |
| 9 | Endovenous therapy of varicose veins: a better outcome than standard surgery? 显示文摘 | AI Samaraee A McCallum IJ Mudawi A | 2009 | Surgeon2009，7，3： | 1 |
| 10 | Endovenous therapy of varicose veins:a better outcome than standard surgery显示文摘 | Al Samaraee A McCallum I J Mudawi A | | 0，，： | 1 |
| 11 | Selective site rightventricular pacing 显示文摘 | Albouaini K Alkarmi A Mudawi T | 2009 | Heart2009，95，24： | 1 |
| 12 | New aliphatic ester and new thiophene derivative from the roots of Alhagi maurorum Medik 显示文摘 | Mudawi B M Al-Hazimi H M Abdallah M A | 2007 | J Saudi Chem Soc2007，11，1： | 1 |
| 13 | Selective site right vent'ricularpacing显示文摘 | Albouaini K Alkarmi A Mudawi T | 2009 | Heart2009，95，24： | 1 |
| 14 | Endovenous thera- py of varicose veins : a better outcome than standard surgery 显示文摘 | AI Samaraee A McCallum IJ Mudawi A | 2009 | Surgeon2009，7，3： | 1 |
| 15 | New aliphatic ketone and new aliphatic ester from the roots of Alhagi maurorum Medik 显示文摘 | Marashdah M S Mudawi B M Al-Hazimi H M | 2006 | J Saudi Chem Soc2006，10，3： | 1 |
| 16 | New triglyceride and new aliphatic ester from the roots of Alhagi maurorum Medik 显示文摘 | Marashdah M S Mudawi B M Al-Hazimi H M | 2006 | J Saudi Chem Soc2006，10，2： | 1 |
| 17 | A Novel Human Interaction Framework Using Quadratic Discriminant Analysis with HMM显示文摘Human-human interaction recognition is crucial in computer vision fields like surveillance,human-computer interaction,and social robotics.It enhances systems’ability to interpret and respond to human behavior precisely.This research focuses on recognizing human interaction behaviors using a static image,which is challenging due to the complexity of diverse actions.The overall purpose of this study is to develop a robust and accurate system for human interaction recognition.This research presents a novel image-based human interaction recognition method using a Hidden Markov Model(HMM).The technique employs hue,saturation,and intensity(HSI)color transformation to enhance colors in video frames,making them more vibrant and visually appealing,especially in low-contrast or washed-out scenes.Gaussian filters reduce noise and smooth imperfections followed by silhouette extraction using a statistical method.Feature extraction uses the features from Accelerated Segment Test(FAST),Oriented FAST,and Rotated BRIEF(ORB)techniques.The application of Quadratic Discriminant Analysis(QDA)for feature fusion and discrimination enables high-dimensional data to be effectively analyzed,thus further enhancing the classification process.It ensures that the final features loaded into the HMM classifier accurately represent the relevant human activities.The impressive accuracy rates of 93%and 94.6%achieved in the BIT-Interaction and UT-Interaction datasets respectively,highlight the success and reliability of the proposed technique.The proposed approach addresses challenges in various domains by focusing on frame improvement,silhouette and feature extraction,feature fusion,and HMM classification.This enhances data quality,accuracy,adaptability,reliability,and reduction of errors. | Tanvir Fatima Naik Bukht Naif Al Mudawi Saud S.Alotaibi Abdulwahab Alazeb Mohammed Alonazi Aisha Ahmed AlArfaj Ahmad Jalal Jaekwang Kim | 2023 | Computers, Materials & Continua2023，77，11： | 0 |
| 18 | Road Traffic Monitoring from Aerial Images Using Template Matching and Invariant Features显示文摘Road traffic monitoring is an imperative topic widely discussed among researchers.Systems used to monitor traffic frequently rely on cameras mounted on bridges or roadsides.However,aerial images provide the flexibility to use mobile platforms to detect the location and motion of the vehicle over a larger area.To this end,different models have shown the ability to recognize and track vehicles.However,these methods are not mature enough to produce accurate results in complex road scenes.Therefore,this paper presents an algorithm that combines state-of-the-art techniques for identifying and tracking vehicles in conjunction with image bursts.The extracted frames were converted to grayscale,followed by the application of a georeferencing algorithm to embed coordinate information into the images.The masking technique eliminated irrelevant data and reduced the computational cost of the overall monitoring system.Next,Sobel edge detection combined with Canny edge detection and Hough line transform has been applied for noise reduction.After preprocessing,the blob detection algorithm helped detect the vehicles.Vehicles of varying sizes have been detected by implementing a dynamic thresholding scheme.Detection was done on the first image of every burst.Then,to track vehicles,the model of each vehicle was made to find its matches in the succeeding images using the template matching algorithm.To further improve the tracking accuracy by incorporating motion information,Scale Invariant Feature Transform(SIFT)features have been used to find the best possible match among multiple matches.An accuracy rate of 87%for detection and 80%accuracy for tracking in the A1 Motorway Netherland dataset has been achieved.For the Vehicle Aerial Imaging from Drone(VAID)dataset,an accuracy rate of 86%for detection and 78%accuracy for tracking has been achieved. | Asifa Mehmood Qureshi Naif Al Mudawi Mohammed Alonazi Samia Allaoua Chelloug Jeongmin Park | 2024 | Computers, Materials & Continua2024，78，3： | 0 |
| 19 | IoT and Blockchain-Based Mask Surveillance System for COVID-19 Prevention Using Deep Learning显示文摘On the edge of the worldwide public health crisis,the COVID-19 disease has become a serious headache for its destructive nature on humanity worldwide.Wearing a facial mask can be an effective possible solution to mitigate the spreading of the virus and reduce the death rate.Thus,wearing a face mask in public places such as shopping malls,hotels,restaurants,homes,and offices needs to be enforced.This research work comes up with a solution of mask surveillance system utilizing the mechanism of modern computations like Deep Learning(DL),Internet of things(IoT),and Blockchain.The absence or displacement of the mask will be identified with a raspberry pi,a camera module,and the operations of DL and Machine Learning(ML).The detected information will be sent to the cloud server with the mechanism of IoT for real-time data monitoring.The proposed model also includes a Blockchain-based architecture to secure the transactions of mask detection and create efficient data security,monitoring,and storage fromintruders.This research further includes an IoT-based mask detection scheme with signal bulbs,alarms,and notifications in the smartphone.To find the efficacy of the proposed method,a set of experiments has been enumerated and interpreted.This research work finds the highest accuracy of 99.95%in the detection and classification of facial masks.Some related experiments with IoT and Block-chain-based integration have also been performed and calculated the corresponding experimental data accordingly.ASystemUsability Scale(SUS)has been accomplished to check the satisfaction level of use and found the SUS score of 77%.Further,a comparison among existing solutions on three emergent technologies is included to track the significance of the proposed scheme.However,the proposed system can be an efficient mask surveillance system for COVID-19 and workable in real-time mask detection and classification. | Wahidur Rahman Naif Al Mudawi Abdulwahab Alazeb Muhammad Minoar Hossain Saima Siddique Tashfia MdTarequl Islam Shisir Mia Mohammad Motiur Rahman | 2022 | Computers, Materials & Continua2022，，7： | 0 |
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