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X-ray Image-Based COVID-19 Patient Detection Using Machine Learning-Based Techniques

Computer Systems Science & Engineering 2022年第11期43卷 671-682页

作者： Shabana Habib saleh alyahya Aizaz Ahmed Muhammad Islam Sheroz Khan Ishrat Khan Muhammad Kamil Department of Information Technology College of ComputerQassim UniversityBuraidah52571Saudi Arabia Department of Electrical Engineering College of Engineering&Information TechnologyOnaizah CollegesOnaizah51911Saudi Arabia Digital Image Processing Lab Islamia CollegePeshawar25120KPKPakistan Department of Computer Science College of Computer and Information SciencesPrince Sultan UniversityRiyadh11586Saudi Arabia Department of Electrical Engineering National University of Computer and Emerging SciencesPeshawarPakistan

In early December 2019,the city of Wuhan,China,reported an outbreak of coronavirus disease(COVID-19),caused by a novel severe acute respiratory syndrome coronavirus-2(SARS-CoV-2).On January 30,2020,the World Health Organization(WHO)declared the outbreak a global pandemic *** the face of the COVID-19 pandemic,the most important step has been the effective diagnosis and monitoring of infected *** COVID-19 using Machine Learning(ML)technologies can help the health care unit through assistive diagnostic suggestions,which can reduce the health unit's burden to a certain *** paper investigates the possibilities of ML techniques in identifying/detecting COVID-19 patients including both conventional and exploring from chest X-ray images the effect of viral *** approach includes preprocessing,feature extraction,and ***,the features are extracted using the Histogram of Oriented(HOG)and Local Binary Pattern(LBP)feature ***,for the extracted features classification,six ML models of Support Vector Machine(SVM)and K-Nearest Neighbor(KNN)is *** results show that the diagnostic accuracy of random forest classifier(RFC)on extracted HOG plusLBP features is as high as 94%followed by SVM at 93%.The sensitivity of the K-nearest neighbour model has reached an accuracy of 88%.Overall,the predicted approach has shown higher classification accuracy and effective diagnostic *** is a highly useful tool for clinical practitioners and radiologists to help them in diagnosing and tracking the cases of COVID-19.

关键词： Image pre-processing detection classification x-ray images filter

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Saudi Consensus for GLP-1 RAs Switching Guidance: Consensus Report

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International Journal of Clinical Medicine 2022年第1期13卷 22-35页

作者： Saud Alsifri Hussein Elbadawi Fahad Alsabaan Abdulraouf Almahfouz Khalid alyahya Eman Shesha Laila Abu Esba Meshal Alnais Raed Aldahash Turky Alharbi saleh Aljaser Emad R. Issak Endocrinology Department Alhada & Taif Armed Forces Hospitals Taif Saudi Arabia My Clinic Medical Center Jeddah Saudi Arabia Endocrinology Department Security Forces Hospital Riyadh Saudi Arabia Section of Endocrinology Department of Medicine The King Faisal Specialist Hospital and Research Centre Riyadh Saudi Arabia Pharmacy Department Prince Sultan Military Medical City Riyadh Saudi Arabia Diabetes Center King Salman Hospital Riyadh Saudi Arabia King Abdulaziz Medical City Riyadh Saudi Arabia Internal Medicine and Diabetes King Khalid Hospital Hail Saudi Arabia Department of Medicine King Abdulaziz Medical City National Guard Riyadh Saudi Arabia Family Medicine Department Prince Sultan Military Medical City Riyadh Saudi Arabia King Saud bin Abdulaziz University for Health Science Riyadh Saudi Arabia Medicine Department Faculty of Medicine Ain-Shams University Cairo Egypt

Glucagon-like peptide-1 receptor agonists (GLP-1RAs) provide adequate glycemic control, weight reduction, low risk of hypoglycemia, and CV risk reduction. Their usage for type 2 DM (T2DM) is recommended mainly when hypoglycemia or weight gain should be considered, also, whenever initial therapy is failed. There are many recent updates in the treatment paradigm of T2DM. There are many types of GLP-1RAs, with a knowledge gap regarding switching between the different types. A Saudi task force gathered to develop an explicit, evidence-based consensus for switching between GLP-1RAs, when, why, and how? This article contains the expert panel’s recommendations as a contribution to complement the knowledge gap in this area from the national perspective. As an alternative to intensifying therapy, switching from one GLP-1RA to another has various advantages. Improvements in glycemic control, weight loss, adherence, and medications with established cardiovascular benefits are among them. Also, switching needs to be individualized upon many discussed factors like the dose of the previous GLP1-RA and gastrointestinal adverse effects. Discussion with patients about the why and how to switch is critical.

关键词： Glucagon-Like Peptide-1 Receptor Agonists Switching Type 2 DM Glycemic Control

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