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Application of Deep Learning for Fast Detection of COVID-19 in X-Rays using nCOVnet
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| Presently, COVID-19 has posed a serious threat to researchers, scientists, health professionals, and administrations around the globe from its detection to its treatment. The whole world is witnessing a lockdown like situation because of COVID-19 pandemic. Persistent efforts are being made by the researchers to obtain ... |
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Low-cost thermal imaging with machine learning for non-invasive diagnosis and therapeutic monitoring of pneumonia
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| Rapid screening and early treatment of lung infection are essential for effective control of many epidemics such as Coronavirus Disease 2019 (COVID-19). Recent studies have demonstrated the potential correlation between lung infection and the change of back skin temperature distribution. Based on these findings, we pro... |
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Triage of potential COVID-19 patients from chest X-ray images using hierarchical convolutional networks
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| The current COVID-19 pandemic has motivated the researchers to use artificial intelligence techniques for a potential alternative to reverse transcription-polymerase chain reaction due to the limited scale of testing. The chest X-ray (CXR) is one of the alternatives to achieve fast diagnosis, but the unavailability of ... |
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Rapid identification of COVID-19 severity in CT scans through classification of deep features.
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| BACKGROUND Chest CT is used for the assessment of the severity of patients infected with novel coronavirus 2019 (COVID-19). We collected chest CT scans of 202 patients diagnosed with the COVID-19, and try to develop a rapid, accurate and automatic tool for severity screening follow-up therapeutic treatment. METHODS A t... |
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Machine Learning and Image Analysis Applications in the Fight against COVID-19 Pandemic: Datasets, Research Directions, Challenges and Opportunities
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| COVID-19 pandemic has become the most devastating disease of the current century and spread over 216 countries around the world. The disease is spreading through outbreaks despite the availability of modern sophisticated medical treatment. Machine Learning and Image Analysis research has been making great progress in m... |
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Lightweight Deep Learning Model for Automated COVID-19 Diagnosis from CXR Images
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| The novel coronavirus has caused a huge number of infections and continues to be a concern. Rapid detection of infection is paramount in order to (i) ensure timely quarantine and segregation, and (ii) to plan suitable treatment trajectories. The conventional RT-PCR test for COVID-19 is both expensive and slow. Therefor... |
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Covid prediction from x-ray images
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| Early detection of COVID 19 is having the significant impact on curtailing the COVID 19 transmission at faster rate and is the need of the hour An Artificial Intelligence diagnostic using Deep Learning models trained with X ray images of COVID infected and noninfected patients is a new promising method that helps in ea... |
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CxSE: Chest X-ray Slow Encoding CNN forCOVID-19 Diagnosis
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| The coronavirus continues to disrupt our everyday lives as it spreads at an exponential rate. It needs to be detected quickly in order to quarantine positive patients so as to avoid further spread. This work proposes a new convolutional neural network (CNN) architecture called 'slow Encoding CNN. The proposed model's b... |
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Establishing Classifiers With Clinical Laboratory Indicators to Distinguish COVID-19 From Community-Acquired Pneumonia: Retrospective Cohort Study
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| BACKGROUND: The initial symptoms of patients with COVID-19 are very much like those of patients with community-acquired pneumonia (CAP); it is difficult to distinguish COVID-19 from CAP with clinical symptoms and imaging examination. OBJECTIVE: The objective of our study was to construct an effective model for the earl... |
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Coronavirus disease analysis using chest X-ray images and a novel deep convolutional neural network
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| BACKGROUND: The recent emergence of a highly infectious and contagious respiratory viral disease known as COVID-19 has vastly impacted human lives and overloaded the health care system. Therefore, it is crucial to develop a fast and accurate diagnostic system for the timely identification of COVID-19 infected patients ... |
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Deteksi Penyakit COVID-19 Berdasarkan Citra X-Ray Menggunakan Deep Residual Network
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| Penyakit Coronavirus-2019 atau COVID-19 telah menjadi pandemi global dan menjadi masalah utama yang harus segera dikendalikan. Salah satu cara yang dapat dilakukan adalah memutus rantai penyebaran virus tersebut dengan melakukan deteksi dan melalukan karantina. Pencitraan X-Ray dapat dijadikan alternatif dalam mempelaj... |
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Rapid Artificial Intelligence Solutions in a Pandemic - The COVID-19-20 Lung CT Lesion Segmentation Challenge
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| Artificial intelligence (AI) methods for the automatic detection and quantification of COVID-19 lesions in chest computed tomography (CT) might play an important role in the monitoring and management of the disease. We organized an international challenge and competition for the development and comparison of AI algorit... |
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Prior-Attention Residual Learning for More Discriminative COVID-19 Screening in CT Images
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| We propose a conceptually simple framework for fast COVID-19 screening in 3D chest CT images. The framework can efficiently predict whether or not a CT scan contains pneumonia while simultaneously identifying pneumonia types between COVID-19 and Interstitial Lung Disease (ILD) caused by other viruses. In the proposed m... |
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Comparing CT scan and chest X-ray imaging for COVID-19 diagnosis
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| People suspected of having COVID-19 need to know quickly if they are infected, so they can receive appropriate treatment, self-isolate, and inform those with whom they have been in close contact. Currently, the formal diagnosis of COVID-19 requires a laboratory test (RT-PCR) on samples taken from the nose and throat. T... |
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Comparison of Classification Algorithms for COVID19 Detection using Cough Acoustic Signals (preprint)/ en
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| The epidemic disease, called the new coronavirus (COVID19), firstly occurred in Wuhan, China in December 2019. COVID19 was announced as an epidemic by World Health Organization soon after. Some of the symptoms of this disease are fever, cough, shortness of breath and difficulty in breathing. In more severe cases, death... |
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A novel deep learning based method for COVID-19 detection from CT image
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| The novel Coronavirus named COVID-19 that World Health Organization (WHO) announced as a pandemic rapidly spread worldwide. Fast diagnosis of the virus infection is critical to prevent further spread of the virus, help identify the infected population, and cure the patients. Due to the increasing rate of infection and ... |
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COVID19 Chest X-Ray Classification with Simple Convolutional Neural Network
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| COVID-19 outbreak calls for the urgent need of quick, accurate, and accessible methods for detection Convolutional neural networks applied to chest X-ray images is a promising solution;however, X-ray device configurations vary and data quality across different datasets are inconsistent This leads to overfitting on a pa... |
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Automated diagnosis of COVID-19 with limited posteroanterior chest X-ray images using fine-tuned deep neural networks
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| The novel coronavirus 2019 (COVID-19) is a respiratory syndrome that resembles pneumonia. The current diagnostic procedure of COVID-19 follows reverse-transcriptase polymerase chain reaction (RT-PCR) based approach which however is less sensitive to identify the virus at the initial stage. Hence, a more robust and alte... |
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Real-Time Diagnosis System of COVID-19 Using X-Ray Images and Deep Learning
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| The novel coronavirus named COVID-19 has quickly spread among humans worldwide, and the situation remains hazardous to the health system. The existence of this virus in the human body is identified through sputum or blood samples. Furthermore, computed tomography (CT) or X-ray has become a significant tool for quick di... |
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Recognition of the standardization of wearing masks during the epidemic of COVID-19
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| In face of COVID-19, it is very important to wear masks in public In this article, we use a kind of improved convolutional neural network algorithm DFS (detection with feature fusion and segmentation supervision) for face detection, and YCrCb elliptic skin color model is used for mask recognition We expect to better su... |
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Efficient intelligent system for diagnosis pneumonia (SARSCOVID19) in X-ray images empowered with initial clustering
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| This paper proposes efficient models to help diagnose respiratory (SARSCOVID19) infections by developing new data descriptors for standard machine learning algorithms using X-Ray images As COVID-19 is a significantly serious respiratory infection that might lead to losing life, artificial intelligence plays a main role... |
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Diagnosing COVID-19 on Limited Data: A Comparative Study of Machine Learning Methods
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| Given the enormous impact of COVID-19, effective and early detection of the virus is a crucial research question. In this paper, we compare the effectiveness of several machine learning algorithms in detecting COVID-19 virus based on patient’s age, gender, and nationality. The results of the experiments show that neura... |
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A COMPARATIVE STUDY OF X-RAY AND CT IMAGES IN COVID-19 DETECTION USING IMAGE PROCESSING AND DEEP LEARNING TECHNIQUES
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| The deadly coronavirus has not just devastated the lives of millions but has put the entire healthcare system under tremendous pressure. Early diagnosis of COVID-19 plays a significant role in isolating the positive cases and preventing the further spread of the disease. The medical images along with deep learning mode... |
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Reliability thermal imaging is used to screen employees for a classic sign of COVID-19 infection
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| In the UK, AVT Reliability, a company which provides products and services that focus on helping industry improve plant reliability and manage assets, is using its expertise in thermal imaging – usually employed to detect faults in factory equipment – to help companies protect their workforce |
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Deep Learning Based Early Diagnosis for SARS-CoV-2 Using Chest X-Ray Images
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| Although Vaccines seem like the first ray of hope in a long time, it is still far too early to assume that this pandemic calamity is over. The corona virus is a persistent and highly contagious disease which can evolve faster than most self-acclaimed SoundCloud Rappers’ dying careers. Fortunately, computed tomography (... |
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Deep transfer learning CNN based approach for COVID-19 detection
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| Recently, the novel coronavirus (Covid-19) and its different variants have spread rapidly across the world. Early-stage detection of COVID-19 is a challenging task due to the limited availability of Covid testing kits to the public. Conventionally, reverse transcription-polymerase chain reaction (RTPCR) is the reliable... |
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COV-SNET: A deep learning model for X-ray-based COVID-19 classification
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| The AI research community has recently been intensely focused on diagnosing COVID-19 by applying deep learning technology to the X-ray scans taken of COVID-19 patients. Differentiating COVID-19 from other pneumonia-inducing illnesses is a highly challenging task as it shares many of the same imaging characteristics as ... |
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COVID-19 and Computer Audition: An Overview on What Speech & Sound Analysis Could Contribute in the SARS-CoV-2 Corona Crisis
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| At the time of writing this article, the world population is suffering from more than 2 million registered COVID-19 disease epidemic-induced deaths since the outbreak of the corona virus, which is now officially known as SARS-CoV-2. However, tremendous efforts have been made worldwide to counter-steer and control the e... |
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Cough/X-ray/CT (CXC) website for testing COVID-19 and auto-informing results
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| Despite the development of vaccines and the emergence of various treatments for COVID-19, the number of confirmed cases of the coronavirus disease (COVID-19) is increasing worldwide, and it is unlikely that the disease will ever disappear completely. Having a non-contact remote testing system can improve the workload o... |
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Clinically Applicable AI System for Accurate Diagnosis, Quantitative Measurements and Prognosis of COVID-19 Pneumonia Using Computed Tomography
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| Summary Many COVID-19 patients infected by SARS-CoV-2 virus develop pneumonia (called novel coronavirus pneumonia, NCP) and rapidly progress to respiratory failure. However, rapid diagnosis and identification of high-risk patients for early intervention are challenging. Using a large computed Tomography (CT) database f... |
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Recent Advances in Computer Audition for Diagnosing COVID-19: An Overview
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| Computer audition (CA) has been demonstrated to be efficient in healthcare domains for speech-affecting disorders (e.g., autism spectrum, depression, or Parkinson's disease) and body sound-affecting abnormalities (e. g., abnormal bowel sounds, heart murmurs, or snore sounds). Nevertheless, CA has been underestimated in... |
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Covid-19 Classification Using Deep Learning in Chest X-Ray Images
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| Covid-19 virus, which has emerged in the Republic of China in an undetermined cause, has affected the whole world quickly. It is important to detect positive cases early to prevent further spread of the outbreak. In the diagnostic phase, radiological images of the chest are determinative as well as the RT-PCR (Reverse ... |
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Covid19 identification using machine learning classifiers with histogram of luminance chroma features of chest x-ray images
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| The outbreak of the novel Coronavirus has caused catastrophic consequences on the entire global economy leading to a huge loss of health and wealth Mankind has suffered a lot due to this pandemic Large number of screening tests are performed on the suspected individuals by using Covid-19 test kits As the rate of spread... |
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COVID-CAPS: A Capsule Network-based Framework for Identification of COVID-19 cases from X-ray Images
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| Novel Coronavirus disease (COVID-19) has abruptly and undoubtedly changed the world as we know it at the end of the 2nd decade of the 21st century. COVID-19 is extremely contagious and quickly spreading globally making its early diagnosis of paramount importance. Early diagnosis of COVID-19 enables health care professi... |
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Prediction of COVID Criticality Score with Laboratory, Clinical and CT Images using Hybrid Regression Models
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| Background and Objective: Rapid and precise diagnosis of COVID-19 is very critical in hotspot regions. The main aim of this proposed work is to investigate the baseline, laboratory and CT features of COVID-19 affected patients of two groups (Early and Critical stages). The detection model for COVID-19 is built dependin... |
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DDCNNC: Dilated and Depthwise separable Convolutional Neural Network for diagnosis COVID-19 via Chest X-ray images
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| Purpose As of December 21, 2020, a total of 77,670,400 cases of coronavirus disease 2019 (COVID-19) have been confirmed worldwide, 53,825,243 cases have been cured and 1,693,253 cases have died Among the diagnostic methods of COVID-19, chest X-ray images have the advantages of fast imaging, low cost and high accuracy o... |
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Multi-Stage CNN Architecture for Face Mask Detection
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| The end of 2019 witnessed the outbreak of Coronavirus Disease 2019 (COVID-19), which has continued to be the cause of plight for millions of lives and businesses even in 2020. As the world recovers from the pandemic and plans to return to a state of normalcy, there is a wave of anxiety among all individuals, especially... |
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COVID-19 Disease Diagnosis using Smart Deep Learning Techniques
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| Corona virus is a big family of virus which cans origin disease from communal cold to additional severe disease such as MERS-CoV and SARS-CoV. A coronavirus is a new straining that has not been earlier recognized in humans. Recently, COVID-19 pandemic infection is spreading from human to human rapidly all over the worl... |
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JCS: An Explainable COVID-19 Diagnosis System by Joint Classification and Segmentation
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| Recently, the coronavirus disease 2019 (COVID-19) has caused a pandemic disease in over 200 countries, influencing billions of humans. To control the infection, identifying and separating the infected people is the most crucial step. The main diagnostic tool is the Reverse Transcription Polymerase Chain Reaction (RT-PC... |
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Deep Learning Algorithm for COVID-19 Classification Using Chest X-Ray Images
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| Early diagnosis of the harmful severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), along with clinical expertise, allows governments to break the transition chain and flatten the epidemic curve. Although reverse transcription-polymerase chain reaction (RT-PCR) offers quick results, chest X-ray (CXR) imaging i... |
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Approach for Training Quantum Neural Network to Predict Severity of COVID-19 in Patients
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| Currently, COVID-19 is spreading all over the world and profoundly impacting people’s lives and economic activities In this paper, a novel approach called the COVID-19 Quantum Neural Network (CQNN) for predicting the severity of COVID-19 in patients is proposed It consists of two phases: In the first, the most distinct... |
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COVID19-CT-dataset: an open-access chest CT image repository of 1000+ patients with confirmed COVID-19 diagnosis
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| OBJECTIVES: The ongoing Coronavirus disease 2019 (COVID-19) pandemic has drastically impacted the global health and economy. Computed tomography (CT) is the prime imaging modality for diagnosis of lung infections in COVID-19 patients. Data-driven and Artificial intelligence (AI)-powered solutions for automatic processi... |
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A Generic Deep Learning Based Cough Analysis System from Clinically Validated Samples for Point-of-Need Covid-19 Test and Severity Levels
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| We seek to evaluate the detection performance of a rapid primary screening tool of Covid-19 solely based on the cough sound from 8,380 clinically validated samples with laboratory molecular-test (2,339 Covid-19 positive and 6,041 Covid-19 negative) Samples were clinically labelled according to the results and severity ... |
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A Vision-Based Fruit Packaging Robot
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| The rapid development of computer vision makes human-computer interaction possible and has a wide application prospect. Since the first case of COVID-19 was found, up to now, the global number of infected people has reached 119220681 [1]. In China, although the epidemic is under control, affected by the external enviro... |
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Deep convolutional neural networks approach for classification of lung diseases using x-rays: Covid-19, pneumonia, and tuberculosis
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| In this study, we have proposed a model to identify pulmonary diseases such as COVID-19, pneumonia, and tuberculosis from X-ray images Identifying and differentiating among these diseases is already a hard task for doctors Recent findings obtained using radiology imaging techniques suggest that X-ray images contain sal... |
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Dual-branch combination network (DCN): towards accurate diagnosis and lesion segmentation of COVID-19 using CT images
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| The recent global outbreak and spread of coronavirus disease (COVID-19) makes it an imperative to develop accurate and efficient diagnostic tools for the disease as medical resources are getting increasingly constrained. Artificial intelligence (AI)-aided tools have exhibited desirable potential; for example, chest com... |
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Development and Validation of a Deep Learning-Based Model Using Computed Tomography Imaging for Predicting Disease Severity of Coronavirus Disease 2019
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| OBJECTIVES: Coronavirus disease 2019 (COVID-19) is sweeping the globe and has resulted in infections in millions of people. Patients with COVID-19 face a high fatality risk once symptoms worsen; therefore, early identification of severely ill patients can enable early intervention, prevent disease progression, and help... |
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Does Non-COVID19 Lung Lesion Help? Investigating Transferability in COVID-19 CT Image Segmentation
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| Background and Objective: Coronavirus disease 2019 (COVID-19) is a highly contagious virus spreading all around the world Deep learning has been adopted as an effective technique to aid COVID-19 detection and segmentation from computed tomography (CT) images The major challenge lies in the inadequate public COVID-19 da... |
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Analysis of Separability of COVID-19 and Pneumonia in Chest X-ray Images by Means of Convolutional Neural Networks
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| The new coronavirus (COVID-19) is a disease that is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) On March 11, 2020, the coronavirus outbreak has been labelled a global pandemic by the World Health Organization In this context, chest X-ray imaging has become a remarkably powerful tool for the i... |
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Automated detection of COVID-19 cases using deep neural networks with X-ray images
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| Abstract The novel coronavirus 2019 (COVID-2019), which first appeared in Wuhan city of China in December 2019, spread rapidly around the world and became a pandemic. It has caused a devastating effect on both daily lives, public health, and the global economy. It is critical to detect the positive cases as early as po... |
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Analysis of high-resolution reconstruction of medical images based on deep convolutional neural networks in lung cancer diagnostics.
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| BACKGROUND AND OBJECTIVE To study the diagnostic effect of 64-slice spiral CT and MRI high-resolution images based on deep convolutional neural networks(CNN) in lung cancer. METHODS In this paper, we Select 74 patients with highly suspected lung cancer who were treated in our hospital from January 2017 to January 2021 ... |
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ECOVNet: a highly effective ensemble based deep learning model for detecting COVID-19
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| The goal of this research is to develop and implement a highly effective deep learning model for detecting COVID-19. To achieve this goal, in this paper, we propose an ensemble of Convolutional Neural Network (CNN) based on EfficientNet, named ECOVNet, to detect COVID-19 from chest X-rays. To make the proposed model mo... |
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Comparative performance analysis of the ResNet backbones of Mask RCNN to segment the signs of COVID-19 in chest CT scans
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| COVID-19 has been detrimental in terms of the number of fatalities and rising number of critical patients across the world. According to the UNDP (United National Development Programme) Socio-Economic programme, aimed at the COVID-19 crisis, the pandemic is far more than a health crisis: it is affecting societies and e... |
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Detection System of Wearing Face Masks Normatively Based on Deep Learning
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| The novel coronavirus COVID-19 can be transmitted, for example, by contacting with oral and nasal's secretions, and traditional mask detection algorithms often fail to distinguish whether masks are worn regularly. In this article, we improve the algorithm network structure based on the improved YOLOV3-tiny algorithm an... |
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Detection and screening of COVID-19 through chest computed tomography radiographs using deep neural networks.
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| December 2019 ended with a deadly virus outbreak named as COVID-19 or severe acute respiratory syndrome coronavirus 2 (SARS-COV-2). On January 30th, World Health Organization declared it as a “Public Emergency of International Concern,” which continuous its devastation all over the world. Currently 2,578,996 COVID-19 i... |
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Development Of A Deep Learning Model To Classify X-Ray Of Covid-19, Normal And Pneumonia-Affected Patients
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| Pneumonia is commonly seen in several diseases, including Covid-19 that has put countries under lockdown today [1]. Other than antigen rapid test kit (RTK) and reverse transcription-polymerase chain reaction (RT-PCR), an alternative method to detect COVID-19 is through the examination of patients' chest radiography (CX... |
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A 3D CNN Classification Model for Accurate Diagnosis of Coronavirus Disease 2019 using Computed Tomography Images
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| The coronavirus disease (COVID-19) has been spreading rapidly around the world. As of August 25, 2020, 23.719 million people have been infected in many countries. The cu-mulative death toll exceeds 812,000. Early detection of COVID-19 is essential to provide patients with appropriate medical care and protect uninfected... |
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A Machine Learning System for Awareness, Diagnosing and Predicting COVID-19
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| Technology plays a vital role in our lives, and its role magnifies in crises like the COVID-19 pandemic. Technology reduced the effects of lockdown by helping in education, healthcare, industry sectors. This book chapter introduces an innovative system that uses contemporary machine learning techniques to stop the COVI... |
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An Empirical Study on Detecting COVID-19 in Chest X-ray Images Using Deep Learning Based Methods
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| Spreading of COVID-19 virus has increased the efforts to provide testing kits. Not only the preparation of these kits had been hard, rare, and expensive but also using them is another issue. Results have shown that these kits take some crucial time to recognize the virus, in addition to the fact that they encounter wit... |
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Fully automatic pipeline of convolutional neural networks and capsule networks to distinguish COVID-19 from community-acquired pneumonia via CT images
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| BACKGROUND: Chest computed tomography (CT) is crucial in the diagnosis of coronavirus disease 2019 (COVID-19). However, the persistent pandemic and similar CT manifestations between COVID-19 and community-acquired pneumonia (CAP) raise methodological requirements. METHODS: A fully automatic pipeline of deep learning is... |
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Automatic Segmentation of COVID-19 CT Images using improved MultiResUNet
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| Corona Virus Disease 2019 (COVID-19) has seriously threatened human life and health in just a few months The global economy, education, transportation and other aspects have been affected In order to solve the problems caused by COVID-19 as soon as possible, it is important to quickly and accurately confirm whether peo... |
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Improving performance of CNN to predict likelihood of COVID-19 using chest X-ray images with preprocessing algorithms
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| As the rapid spread of coronavirus disease (COVID-19) worldwide, chest X-ray radiography has also been used to detect COVID-19 infected pneumonia and assess its severity or monitor its prognosis in the hospitals due to its low cost, low radiation dose, and wide accessibility. However, how to more accurately and efficie... |
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Deep Learning Approach for Discovery of In Silico Drugs for Combating COVID-19
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| Early diagnosis of pandemic diseases such as COVID-19 can prove beneficial in dealing with difficult situations and helping radiologists and other experts manage staffing more effectively. The application of deep learning techniques for genetics, microscopy, and drug discovery has created a global impact. It can enhanc... |
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Detection of covid-19 from chest x-ray and ct scan images using improved stacked sparse autoencoder
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| The novel Coronavirus 2019 (COVID-19) has spread rapidly and has become a pandemic around the world. So far, about 44 million cases have been registered, causing more than one million deaths worldwide. COVID-19 has had a devastating impact on every nation, particularly the economic sector. To identify the infected huma... |
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An Integrated Deep Learning and Belief Rule Base Intelligent System to Predict Survival of COVID-19 Patient under Uncertainty
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| The novel Coronavirus-induced disease COVID-19 is the biggest threat to human health at the present time, and due to the transmission ability of this virus via its conveyor, it is spreading rapidly in almost every corner of the globe. The unification of medical and IT experts is required to bring this outbreak under co... |
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Artificial intelligence enabled preliminary diagnosis for COVID-19 from voice cues and questionnairesa)
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| The COVID-19 outbreak was announced as a global pandemic by the World Health Organization in March 2020 and has affected a growing number of people in the past few months. In this context, advanced artificial intelligence techniques are brought to the forefront as a response to the ongoing fight toward reducing the imp... |
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A deep transfer learning based model for automatic detection of COVID-19 from chest X-rays
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| Deep learning in medical imaging has revolutionized the way we interpret medical data, as high computational devices' capabilities are far more than their creators. With the pandemic causing havoc for the second straight year, the findings in our paper will allow researchers worldwide to use and create state-of-the-art... |
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A Light CNN for detecting COVID-19 from CT scans of the chest
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| OVID-19 is a world-wide disease that has been declared as a pandemic by the World Health Organization. Computer Tomography (CT) imaging of the chest seems to be a valid diagnosis tool to detect COVID-19 promptly and to control the spread of the disease. Deep Learning has been extensively used in medical imaging and con... |
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Synergistic learning of lung lobe segmentation and hierarchical multi-instance classification for automated severity assessment of COVID-19 in CT images
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| Understanding chest CT imaging of the coronavirus disease 2019 (COVID-19) will help detect infections early and assess the disease progression. Especially, automated severity assessment of COVID-19 in CT images plays an essential role in identifying cases that are in great need of intensive clinical care. However, it i... |
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A novel artificial intelligence-assisted triage tool to aid in the diagnosis of suspected COVID-19 pneumonia cases in fever clinics
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| Background: Currently, the need to prevent and control the spread of the 2019 novel coronavirus disease (COVID-19) outside of Hubei province in China and internationally has become increasingly critical We developed and validated a diagnostic model that does not rely on computed tomography (CT) images to aid in the ear... |
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Diagnostic classification of coronavirus disease 2019 (COVID-19) and other pneumonias using radiomics features in CT chest images
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| We propose a classification method using the radiomics features of CT chest images to identify patients with coronavirus disease 2019 (COVID-19) and other pneumonias. The chest CT images of two groups of participants (90 COVID-19 patients and 90 other pneumonias patients) were collected, and the two groups of data were... |
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CT-Based COVID-19 triage: Deep multitask learning improves joint identification and severity quantification
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| The current COVID-19 pandemic overloads healthcare systems, including radiology departments. Though several deep learning approaches were developed to assist in CT analysis, nobody considered study triage directly as a computer science problem. We describe two basic setups: Identification of COVID-19 to prioritize stud... |
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Can AI Help in Screening Viral and COVID-19 Pneumonia?
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| Coronavirus disease (COVID-19) is a pandemic disease, which has already caused thousands of causalities and infected several millions of people worldwide. Any technological tool enabling rapid screening of the COVID-19 infection with high accuracy can be crucially helpful to the healthcare professionals. The main clini... |
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Deep learning model to predict the need for mechanical ventilation using chest X-ray images in hospitalised patients with COVID-19
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| Objectives: There exists a wide gap in the availability of mechanical ventilator devices and their acute need in the context of the COVID-19 pandemic An initial triaging method that accurately identifies the need for mechanical ventilation in hospitalised patients with COVID-19 is needed We aimed to investigate if a po... |
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Deep convolutional neural network–based image classification for COVID-19 diagnosis
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| Initial cases of COVID-19 trace back to the end of 2019 which has laid foundations for the extensive spread of the disease risking lives worldwide. In response to the global coronavirus pandemic, early diagnosis of the disease is vital to prevent the virus from being spread to a larger population. Because of the unavai... |
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COVID19: A Natural Language Processing and Ontology Oriented Temporal Case-Based Framework for Early Detection and Diagnosis of Novel Coronavirus
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| Coronavirus, also known as COVID-19, has been declared a pandemic by the World Health Organization (WHO). At the time of conducting this study, it had recorded over 1.6 million cases while more than 105,000 have died due to it, with these figures rising on a daily basis across the globe. The burden of this highly conta... |
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Recognizing COVID-19 from chest X-ray images for people in rural and remote areas based on deep transfer learning model
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| In this article, we propose Deep Transfer Learning (DTL) Model for recognizing covid-19 from chest x-ray images. The latter is less expensive, easily accessible to populations in rural and remote areas. In addition, the device for acquiring these images is easy to disinfect, clean and maintain. The main challenge is th... |
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Convolutional Sparse Support Estimator Based Covid-19 Recognition from X-ray Images
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| Coronavirus disease (Covid-19) has been the main agenda of the whole world since it came in sight in December 2019. It has already caused thousands of causalities and infected several millions worldwide. Any technological tool that can be provided to healthcare practitioners to save time, effort, and possibly lives has... |
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Multi-classifier-based identification of COVID-19 from chest computed tomography using generalizable and interpretable radiomics features
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| PURPOSE: To investigate the efficacy of radiomics in diagnosing patients with coronavirus disease (COVID-19) and other types of viral pneumonia with clinical symptoms and CT signs similar to those of COVID-19. METHODS: Between 18 January 2020 and 20 May 2020, 110 SARS-CoV-2 positive and 108 SARS-CoV-2 negative patients... |
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DDCNNC: Dilated and Depthwise separable Convolutional Neural Network for diagnosis COVID-19 via Chest X-ray images
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| Purpose As of December 21, 2020, a total of 77,670,400 cases of coronavirus disease 2019 (COVID-19) have been confirmed worldwide, 53,825,243 cases have been cured and 1,693,253 cases have died. Among the diagnostic methods of COVID-19, chest X-ray images have the advantages of fast imaging, low cost and high accuracy ... |
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An Introductory Assessment on Computational Algorithm in Initial Finding of COVID-19 Cases
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| This research discusses how to detect coronavirus patients using various target optimization and deep learning methods. This research utilizes the J48 decision tree methodology to describe the extended attributes of X-ray coronagraphs to identify polluted ill persons rapidly and efficiently. The investigation has found... |
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A Histogram-Based Low-Complexity Approach for the Effective Detection of COVID-19 Disease from CT and X-ray Images
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| The global COVID-19 pandemic certainly has posed one of the more difficult challenges for researchers in the current century. The development of an automatic diagnostic tool, able to detect the disease in its early stage, could undoubtedly offer a great advantage to the battle against the pandemic. In this regard, most... |
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Deep Learning Driven Automated Detection of COVID-19 from Radiography Images: A Comparative Analysis
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| The COVID-19 pandemic has wreaked havoc on the whole world, taking over half a million lives and capsizing the world economy in unprecedented magnitudes. With the world scampering for a vaccine, early detection and containment is the only redress. Existing diagnostic technologies with high accuracy like RT-PCRs are exp... |
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Classification of COVID-19 Cases from X-Ray Images Based on a Modified VGG-16 Model
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| COVID-19 is considered one of the most deadly pandemics by the World Health Organization and has claimed the lives of millions around the world. Mechanisms for early diagnosis and detection of this rapidly spreading disease are necessary to save lives. However, the increase in COVID-19 cases requires not relying on tra... |
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Detection and identification of COVID -19 based on chest medical image by using convolutional neural networks
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| Covid-19 pandemic has caused major out-break all around the world. This pandemic out-break requires lot of testing, which is a tedious process. Deep learning is a successful method that has evolved in image category in the past few years. In this work to detects the presence of coronavirus by using deep learning approa... |
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A Transfer Learning-Based Approach with Deep CNN for COVID-19- and Pneumonia-Affected Chest X-ray Image Classification
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| The COVID-19 pandemic creates a significant impact on everyone’s life. One of the fundamental movements to cope with this challenge is identifying the COVID-19-affected patients as early as possible. In this paper, we classified COVID-19, Pneumonia, and Healthy cases from the chest X-ray images by applying the transfer... |
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Determination of the Severity and Percentage of COVID-19 Infection through a Hierarchical Deep Learning System
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| The coronavirus disease 2019 (COVID-19) has caused millions of deaths and one of the greatest health crises of all time. In this disease, one of the most important aspects is the early detection of the infection to avoid the spread. In addition to this, it is essential to know how the disease progresses in patients, to... |
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Identification of COVID-19 samples from chest X-Ray images using deep learning: A comparison of transfer learning approaches
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| BACKGROUND: The novel coronavirus disease 2019 (COVID-19) constitutes a public health emergency globally. The number of infected people and deaths are proliferating every day, which is putting tremendous pressure on our social and healthcare system. Rapid detection of COVID-19 cases is a significant step to fight again... |
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Domain adaptation based self-correction model for COVID-19 infection segmentation in CT images
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| The capability of generalization to unseen domains is crucial for deep learning models when considering real-world scenarios. However, current available medical image datasets, such as those for COVID-19 CT images, have large variations of infections and domain shift problems. To address this issue, we propose a prior ... |
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A Novel Bayesian Optimization-based Machine Learning Framework for COVID-19 Detection from Inpatient Facility Data
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| The whole world faces a pandemic situation due to the deadly virus, namely COVID-19 It takes considerable time to get the virus well-matured to be traced, and during this time, it may be transmitted among other people To get rid of this unexpected situation, quick identification of COVID-19 patients is required We have... |
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Artificial Intelligence and the Control of COVID-19: A Review of Machine and Deep Learning Approaches
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| This study explores the prevalent Machine and Deep Learning approaches for the control of COVID-19. It reveals the impact of Artificial Intelligence in the case prediction, analysis, diagnosis, and treatment of the disease. Apart from discussing four (4) knowledge areas where Machine Learning and Deep Learning approach... |
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Detection of Lung Ultrasound Covid-19 Disease Patients based Convolution Multifacet Analytics using Deep Learning
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| Deep Learning techniques for ultrasound images, from the front end to the most advanced applications, are the potential effect of deep learning methods on many aspects of the analysis of the ultrasound images. The Covid-19 epidemic has exposed global health care vulnerabilities, especially in developing countries. Lung... |
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A computer-aided diagnostic framework for coronavirus diagnosis using texture-based radiomics images
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| The accurate and rapid detection of the novel coronavirus infection, coronavirus is very important to prevent the fast spread of such disease. Thus, reducing negative effects that influenced many industrial sectors, especially healthcare. Artificial intelligence techniques in particular deep learning could help in the ... |
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Improving Classification Model Performance on Chest X-Rays through Lung Segmentation
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| Chest radiography is an effective screening tool for diagnosing pulmonary diseases. In computer-aided diagnosis, extracting the relevant region of interest, i.e., isolating the lung region of each radiography image, can be an essential step towards improved performance in diagnosing pulmonary disorders. Methods: In thi... |
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A deep-learning based multimodal system for Covid-19 diagnosis using breathing sounds and chest X-ray images
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| Covid-19 has become a deadly pandemic claiming more than three million lives worldwide SARS-CoV-2 causes distinct pathomorphological alterations in the respiratory system, thereby acting as a biomarker to aid its diagnosis A multimodal framework (Ai-CovScan) for Covid-19 detection using breathing sounds, chest X-ray (C... |
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Diagnosis of COVID-19 using auditory acoustic cues
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| COVID-19 can be pre-screened based on symptoms and confirmed using other laboratory tests. The cough or speech from patients are also studied in the recent time for detection of COVID-19 as they are indicators of change in anatomy and physiology of the respiratory system. Along this direction, the diagnosis of COVID-19... |
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Convolutional Neural Network-based Model to Detect COVID-19Using Chest X-ray Images
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| COVID-19, a new coronavirus disease, is caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and was declared a pandemic by the World Health Organization (WHO). Since its outbreak in December 2019, the total number of affected cases reported worldwide has exceeded 215 million, and reported death cases... |
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Multi-angle head pose classification with masks based on color texture analysis and stack generalization
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| Summary Head pose classification is an important part of the preprocessing process of face recognition, which can independently solve application problems related to multi-angle But, due to the impact of the COVID-19 coronavirus pandemic, more and more people wear masks to protect themselves, which covering most areas ... |
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Face Mask Detection using Transfer Learning of InceptionV3
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| The world is facing a huge health crisis due to the rapid transmission of coronavirus (COVID-19). Several guidelines were issued by the World Health Organization (WHO) for protection against the spread of coronavirus. According to WHO, the most effective preventive measure against COVID-19 is wearing a mask in public p... |
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Classification of Covid-19 Coronavirus, Pneumonia and Healthy Lungs in CT Scans Using Q-Deformed Entropy and Deep Learning Features
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| Many health systems over the world have collapsed due to limited capacity and a dramatic increase of suspected COVID-19 cases. What has emerged is the need for finding an efficient, quick and accurate method to mitigate the overloading of radiologists’ efforts to diagnose the suspected cases. This study presents the co... |
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