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Comprehensive Survey of Using Machine Learning in the COVID-19 Pandemic

DIAGNOSTICS (2021)

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Article Computer Science, Artificial Intelligence

Early diagnosis of COVID-19-affected patients based on X-ray and computed tomography images using deep learning algorithm

Debabrata Dansana et al.

Summary: The COVID-19 pandemic, which began in December 2019 in China, has rapidly spread worldwide and infected over ten million people. This study explores the binary classification of pneumonia using convolution neural networks on X-ray and CT scan images. The findings show that fine-tuned versions of VGG-19 and Inception_V2 models demonstrate high accuracy rates.

SOFT COMPUTING (2023)

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Article Engineering, Biomedical

Automated Deep Transfer Learning-Based Approach for Detection of COVID-19 Infection in Chest X-rays

N. Narayan Das et al.

Summary: This paper discusses the use of real-time polymerase chain reaction (RT-PCR) and radiological imaging techniques (such as chest X-rays and CT scans) for detecting and diagnosing COVID-19. Chest X-rays are preferred due to their availability, lower cost, and lower ionizing radiation compared to CT scans. The paper aims to develop an automated deep transfer learning-based approach using the extreme version of the Inception (Xception) model for COVID-19 detection in chest X-rays.

IRBM (2022)

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Review Computer Science, Artificial Intelligence

Artificial intelligence (AI) for medical imaging to combat coronavirus disease (COVID-19): a detailed review with direction for future research

Toufique A. Soomro et al.

Summary: This article provides an extensive review of AI-based methods for efficient COVID-19 diagnosis, covering image acquisition, segmentation, classification, and follow-up diagnosis. Research indicates that AI and machine learning technologies have enhanced the accuracy of Covid-19 diagnosis and have successfully worked with minimal data. Future studies may focus on multi-modality models and selecting optimal model architectures to introduce more intelligence to medical systems, capturing disease characteristics through learning from multi-modality data for reliable COVID-19 diagnosis and timely treatment.

ARTIFICIAL INTELLIGENCE REVIEW (2022)

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Review Public, Environmental & Occupational Health

Prevalence of comorbidities among individuals with COVID-19: A rapid review of current literature

Kalpana Thapa Bajgain et al.

Summary: Hypertension, diabetes, and cardiovascular diseases are the most common comorbidities among COVID-19 positive patients across major epicenters worldwide. While having comorbidities is associated with increased disease severity, there is no clear association found between these risk factors and increased risk of fatality.

AMERICAN JOURNAL OF INFECTION CONTROL (2021)

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Article Radiology, Nuclear Medicine & Medical Imaging

Lung Ultrasound Findings in Patients With Coronavirus Disease (COVID-19)

Yao Zhang et al.

Summary: The study found that typical lung ultrasound findings in patients with COVID-19 include B-lines, pulmonary consolidation, and a thickened pleural line. Additionally, the results suggest that lung ultrasound findings can reflect both the infection duration and disease severity.

AMERICAN JOURNAL OF ROENTGENOLOGY (2021)

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Article Biochemistry & Molecular Biology

Classification of the COVID-19 infected patients using DenseNet201 based deep transfer learning

Aayush Jaiswal et al.

Summary: This study aims to utilize pre-trained deep learning architecture for the detection and diagnosis of COVID-19, proposing a Deep Transfer Learning (DTL) model based on DenseNet201. Experimental results show that the proposed model outperforms competitive approaches in COVID-19 chest CT scan images.

JOURNAL OF BIOMOLECULAR STRUCTURE & DYNAMICS (2021)

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Article Computer Science, Artificial Intelligence

Deep transfer learning-based automated detection of COVID-19 from lung CT scan slices

Sakshi Ahuja et al.

Summary: In this research, transfer learning from CT scan images is used to detect COVID-19 with different pre-trained architectures, the results show that the ResNet18 model offers better classification accuracy compared to other alternatives.

APPLIED INTELLIGENCE (2021)

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Article Computer Science, Artificial Intelligence

COVID-19 open source data sets: a comprehensive survey

Junaid Shuja et al.

Summary: The emergence of the novel virus COVID-19 in Wuhan, China in December 2019 has led to a global crisis of significant proportions. Scientists have been utilizing computer-aided digital technologies to analyze data and come up with solutions, particularly in the areas of statistical and Artificial Intelligence-based analysis. Open source data and code play a crucial role in facilitating collaboration and extending research efforts in the fight against the COVID-19 pandemic.

APPLIED INTELLIGENCE (2021)

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Article Medical Laboratory Technology

Development, evaluation, and validation of machine learning models for COVID-19 detection based on routine blood tests

Federico Cabitza et al.

Summary: The study found that machine learning models can identify COVID-19 positive patients quickly and economically using blood test data. ML can serve as an alternative method to rRT-PCR, especially beneficial for resource-constrained countries.

CLINICAL CHEMISTRY AND LABORATORY MEDICINE (2021)

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Article Environmental Sciences

COVID-19 pandemic: environmental and social factors influencing the spread of SARS-CoV-2 in Sao Paulo, Brazil

Liane Yuri Kondo Nakada et al.

Summary: The study found that the spread of COVID-19 in the expanded metropolitan area of Sao Paulo is directly associated with the availability of highways, positively correlated with population density, negatively correlated with social isolation rate, and inversely correlated with temperature and UV radiation. This suggests that sunlight might contribute to reducing the infectivity of SARS-CoV-2.

ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH (2021)

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Article Infectious Diseases

Older age groups and country-specific case fatality rates of COVID-19 in Europe, USA and Canada

Christian Hoffmann et al.

Summary: The study found that the country-specific case fatality rate of COVID-19 is largely determined by the proportion of older individuals who are diagnosed with SARS-CoV-2. The age distribution of SARS-CoV-2 infections is not uniform, emphasizing the need for detailed demographic data in all analyses on COVID-19 mortality.

INFECTION (2021)

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Article Medicine, General & Internal

The role of lung ultrasound as a frontline diagnostic tool in the era of COVID-19 outbreak

Cristina Sorlini et al.

Summary: This study evaluated the diagnostic accuracy of lung point-of-care ultrasound (POCUS) for suspected SARS-CoV-2 pneumonia in emergency department (ED) patients. The results showed that in this setting, lung POCUS is a sensitive first-line screening tool for patients with symptoms suggestive of SARS-CoV-2 infection.

INTERNAL AND EMERGENCY MEDICINE (2021)

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Article Pathology

Development of a prognostic model for mortality in COVID-19 infection using machine learning

Adam L. Booth et al.

Summary: This study aimed to identify prognostic serum biomarkers in COVID-19 patients at high risk of mortality using a machine learning model, achieving high prediction accuracy. This is crucial for timely and effective management during the pandemic.

MODERN PATHOLOGY (2021)

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Article Biochemistry & Molecular Biology

GESS: a database of global evaluation of SARS-CoV-2/hCoV-19 sequences

Shuyi Fang et al.

Summary: GESS is a resource based on comprehensive analysis of high-quality SARS-CoV-2 genomes, revealing geographical distributions and evolution patterns of SNVs, providing directive information for public health policies and vaccine designs.

NUCLEIC ACIDS RESEARCH (2021)

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Article Engineering, Industrial

A dynamical model of SARS-CoV-2 based on people flow networks

Victoria Lopez et al.

Summary: This study introduces a new dynamical model based on flow networks to measure the severity of the COVID-19 pandemic and simulate the evolution of infected individuals among different states. The model combines elements of the well-known SIR family model and utilizes open government data to illustrate pandemic trends. Additionally, a danger index (DI) is proposed alongside the RO index to further analyze the impact of government policies on pandemic control.

SAFETY SCIENCE (2021)

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Article Computer Science, Artificial Intelligence

Fast deep learning computer-aided diagnosis of COVID-19 based on digital chest x-ray images

Mugahed A. Al-antari et al.

Summary: COVID-19 is a novel harmful respiratory disease that emerged in Wuhan, China and quickly spread worldwide. A deep learning CAD system based on simultaneous detection and classification of COVID-19 achieved high accuracy in differentiating it from other respiratory diseases. The proposed CAD system can make real-time predictions and potentially assist healthcare systems, patients, and physicians in practical applications.

APPLIED INTELLIGENCE (2021)

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Article Computer Science, Artificial Intelligence

AI-assisted CT imaging analysis for COVID-19 screening: Building and deploying a medical AI system

Bo Wang et al.

Summary: This paper presents the experience of building and deploying an AI system for rapid detection of COVID-19 pneumonia, which can save time for physicians and improve the performance of COVID-19 detection. The authors overcame various challenges in a interdisciplinary team and successfully deployed the system in four weeks.

APPLIED SOFT COMPUTING (2021)

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Article Computer Science, Artificial Intelligence

How artificial intelligence and machine learning can help healthcare systems respond to COVID-19

Mihaela van der Schaar et al.

Summary: The COVID-19 pandemic poses threats to global health and economies, requiring the use of modern technologies like machine learning and artificial intelligence to address challenges. Only through intelligently utilizing data resources, developing personalized plans, and expediting clinical trials can the pandemic be effectively tackled.

MACHINE LEARNING (2021)

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Article Neurosciences

Predicting brain age with complex networks: From adolescence to adulthood

Loredana Bellantuono et al.

Summary: Recent studies show that machine learning and deep learning can accurately predict brain age. The proposed method based on complex networks is accurate, robust, and computationally efficient, achieving a high correlation and low error in age prediction. The network model provides new insights on aging patterns in the brain and specific anatomical changes.

NEUROIMAGE (2021)

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Review Endocrinology & Metabolism

Obesity and COVID-19 in Latin America: A tragedy of two pandemics-Official document of the Latin American Federation of Obesity Societies

Bruno Halpern et al.

Summary: Latin America has become the epicenter of the COVID-19 pandemic in May 2020, where obesity and its comorbidities are increasingly prevalent, particularly among individuals with lower income, and are now associated with COVID-19 severity and death. Despite social disparities and poor healthcare access, public health and individual recommendations should focus on addressing the obesity issue in this region.

OBESITY REVIEWS (2021)

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Article Biochemical Research Methods

Deep Learning Enables Accurate Diagnosis of Novel Coronavirus (COVID-19) With CT Images

Ying Song et al.

Summary: The emergence of COVID-19 has led to the urgent need for accurate diagnoses through CT scans. Researchers have developed a deep learning-based CT diagnosis system to accurately identify COVID-19 patients, achieving high levels of accuracy and reliability.

IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS (2021)

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Article Computer Science, Artificial Intelligence

A Comprehensive Survey on Graph Neural Networks

Zonghan Wu et al.

Summary: This article provides a comprehensive overview of graph neural networks (GNNs) in data mining and machine learning fields. It discusses the taxonomy of GNNs, their applications, and summarizes open-source codes, benchmark data sets, and model evaluation. The article also proposes potential research directions in this rapidly growing field.

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2021)

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Article Medicine, General & Internal

LungINFseg: Segmenting COVID-19 Infected Regions in Lung CT Images Based on a Receptive-Field-Aware Deep Learning Framework

Vivek Kumar Singh et al.

Summary: COVID-19 is rapidly spreading worldwide with limited facilities in hospitals, making early identification crucial due to the lack of a vaccine or medicine. This study proposes LungINFseg, a deep learning-based method that effectively segments COVID-19 infections in lung CT images, outperforming 13 other state-of-the-art segmentation methods.

DIAGNOSTICS (2021)

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Article Biology

Estimating and explaining the spread of COVID-19 at the county level in the USA

Anthony R. Ives et al.

Summary: The basic reproduction number, R-0, is crucial for planning public health interventions, and factors such as outbreak timing, population size, density, and spatial location play a significant role in determining the spread rate of COVID-19 in the USA. Population density and spatial location are important predictors for future spread, with SARS-CoV-2 strains impacting transmission rates.

COMMUNICATIONS BIOLOGY (2021)

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Review Hematology

Association between ABO blood types and coronavirus disease 2019 (COVID-19), genetic associations, and underlying molecular mechanisms: a literature review of 23 studies

Yujia Zhang et al.

Summary: Recent studies have shown a correlation between ABO blood types and COVID-19 infection rate, symptoms, and outcomes, with blood type O potentially serving as a protective factor against infection.

ANNALS OF HEMATOLOGY (2021)

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Article Infectious Diseases

Seroprevalence of SARS-CoV-2 (COVID-19) among healthcare workers in Saudi Arabia: comparing case and control hospitals

Haleema Ali Alserehi et al.

Summary: The seropositivity rate among healthcare workers in Saudi Arabia is low, with significant regional variation and higher positivity in case-hospitals compared to control hospitals. Around 8% of the samples tested lacked neutralizing antibodies, indicating potential limitations or cross-reactions in the assays.

DIAGNOSTIC MICROBIOLOGY AND INFECTIOUS DISEASE (2021)

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Article Radiology, Nuclear Medicine & Medical Imaging

A deep learning algorithm using CT images to screen for Corona virus disease (COVID-19)

Shuai Wang et al.

Summary: This study utilized artificial intelligence to extract radiological features from CT images of COVID-19, achieving timely and accurate diagnosis of the disease, demonstrating the feasibility of using AI for disease control.

EUROPEAN RADIOLOGY (2021)

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Article Computer Science, Artificial Intelligence

Deep learning approaches for COVID-19 detection based on chest X-ray images

Aras M. Ismael et al.

Summary: COVID-19 is a novel virus that has led to a global pandemic, with daily increases in cases and deaths. Deep learning approaches, including deep feature extraction and fine-tuning of pretrained convolutional neural networks, show potential in detecting COVID-19 based on chest X-ray images.

EXPERT SYSTEMS WITH APPLICATIONS (2021)

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Article Chemistry, Medicinal

De novo design of new chemical entities for SARS-CoV-2 using artificial intelligence

Navneet Bung et al.

Summary: In this study, deep neural network-based generative and predictive models were used to design 33 potential compounds capable of inhibiting the 3CL protease of SARS-CoV-2. The generative model was optimized using transfer learning and reinforcement learning to focus around the chemical space corresponding to the protease inhibitors.

FUTURE MEDICINAL CHEMISTRY (2021)

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Article Computer Science, Interdisciplinary Applications

Viral Pneumonia Screening on Chest X-Rays Using Confidence-Aware Anomaly Detection

Jianpeng Zhang et al.

Summary: Clusters of viral pneumonia cases over a short period may indicate an outbreak. The study proposes a method to detect viral pneumonia using chest X-rays, which performs well on two different datasets without fine-tuning.

IEEE TRANSACTIONS ON MEDICAL IMAGING (2021)

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Article Engineering, Biomedical

Large-scale screening to distinguish between COVID-19 and community-acquired pneumonia using infection size-aware classification

Feng Shi et al.

Summary: The study proposed an infection size-aware random forest method for discriminating between COVID-19 and CAP patients, showing promising performance in experimental results and potential in assisting clinical decision-making.

PHYSICS IN MEDICINE AND BIOLOGY (2021)

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Article Multidisciplinary Sciences

Potential neutralizing antibodies discovered for novel corona virus using machine learning

Rishikesh Magar et al.

Summary: Researchers used a variety of machine learning models to predict synthetic antibodies that can inhibit SARS-CoV-2, and identified nine stable antibodies that potentially inhibit the virus. They combined bioinformatics, structural biology, and Molecular Dynamics simulations to verify the stability of these candidate antibodies.

SCIENTIFIC REPORTS (2021)

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Article Biology

An analytical study of the factors that influence COVID-19 spread

Kawther Aabed et al.

Summary: The study explores the relationship between COVID-19 and environmental factors, revealing higher growth rates in temperate zones in the Northern Hemisphere and lower rates in tropical zones. The results suggest that the relationship between the epidemic and factors such as air pollution, sea level, and population is resistant to confounding effects.

SAUDI JOURNAL OF BIOLOGICAL SCIENCES (2021)

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Article Construction & Building Technology

Deep learning and medical image processing for coronavirus (COVID-19) pandemic: A survey

Sweta Bhattacharya et al.

Summary: The COVID-19 outbreak since December 2019 has had a significant impact globally. Deep learning has played a crucial role in healthcare applications, aiding in response to the pandemic. Case studies of deep learning applications in different countries help showcase its value in medical image processing.

SUSTAINABLE CITIES AND SOCIETY (2021)

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Article Oncology

A novel artificial intelligence-assisted triage tool to aid in the diagnosis of suspected COVID-19 pneumonia cases in fever clinics

Cong Feng et al.

Summary: A diagnostic model independent of CT images was developed and validated to early identify suspected COVID-19 pneumonia patients upon admission, achieving high performance and deployed as an online triage tool.

ANNALS OF TRANSLATIONAL MEDICINE (2021)

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Article Medicine, General & Internal

A follow-up study shows that recovered patients with re-positive PCR test in Wuhan may not be infectious

Xiaomin Wu et al.

Summary: This retrospective study in Wuhan analyzed the epidemiological and clinical features of 20219 COVID-19 patients and found that a small percentage of recovered patients had a re-positive PCR test for the virus, but close contacts of these cases tested negative.

BMC MEDICINE (2021)

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Article Engineering, Biomedical

Digital imaging, technologies and artificial intelligence applications during COVID-19 pandemic

Mustafa Alhasan et al.

Summary: This study seeks to explore the trends of modern healthcare technologies and Artificial Intelligence during the COVID-19 crisis, define the role of AI in mitigating COVID-19, investigate the efficacy of AI-enabled technology in medical imaging amidst COVID-19, and determine the advantages, drawbacks, and challenges of artificial intelligence during the COVID-19 pandemic.

COMPUTERIZED MEDICAL IMAGING AND GRAPHICS (2021)

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Article Clinical Neurology

Management of COVID-19 in patients with seizures: Mechanisms of action of potential COVID-19 drug treatments and consideration for potential drug-drug interactions with anti-seizure medications

Shreshta Jain et al.

Summary: When it comes to potential therapeutic options for COVID-19 management and potential drug-drug interactions between antiseizure drugs and COVID-19 candidate drugs, further research and experimental results support are needed.

EPILEPSY RESEARCH (2021)

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Article Computer Science, Artificial Intelligence

Automatic detection of coronavirus disease (COVID-19) using X-ray images and deep convolutional neural networks

Ali Narin et al.

Summary: The 2019 novel coronavirus disease has rapidly spread worldwide, with nearly 101,917,147 cases reported, leading to a limited availability of COVID-19 test kits in hospitals. To address this, an automatic detection system using pre-trained convolutional neural network-based models was proposed for detecting coronavirus pneumonia-infected patients. Among the five models tested, ResNet50 demonstrated the highest accuracy in classifying COVID-19 patients from X-ray images.

PATTERN ANALYSIS AND APPLICATIONS (2021)

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Article Public, Environmental & Occupational Health

Nationwide Seroprevalence of SARS-CoV-2 in Saudi Arabia

Naif Khalaf Alharbi et al.

Summary: This study reports the national serological prevalence of SARS-CoV-2 in Saudi Arabia during the COVID-19 pandemic to be 11%, with apparent disparities between regions, indicating the presence of asymptomatic or mild unreported COVID-19 cases.

JOURNAL OF INFECTION AND PUBLIC HEALTH (2021)

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Review Medicine, General & Internal

Mobile Health in Remote Patient Monitoring for Chronic Diseases: Principles, Trends, and Challenges

Nora El-Rashidy et al.

Summary: Remote patient monitoring technology utilizes wearable sensors and communication protocols to monitor patient vital signs in real time, aiding physicians in making timely and accurate diagnostic and treatment decisions. Research based on literature from five databases confirms the effectiveness of remote patient monitoring technology in improving healthcare delivery, increasing diagnosis speed, and reducing costs.

DIAGNOSTICS (2021)

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Article Psychiatry

Mental health issues among health care workers during the COVID-19 pandemic - A study from India

Rajani Parthasarathy et al.

Summary: This study highlights the high prevalence of anxiety and depression among healthcare workers in Karnataka State, India, especially those with frontline COVID-19 responsibilities. Interventions should be implemented to address the mental health concerns of these healthcare workers.

ASIAN JOURNAL OF PSYCHIATRY (2021)

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Letter Medicine, General & Internal

Association of Sociodemographic Factors and Blood Group Type With Risk of COVID-19 in a US Population

Jeffrey L. Anderson et al.

JAMA NETWORK OPEN (2021)

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Editorial Material Engineering, Biomedical

Recent advances in artificial intelligence for cardiac imaging

Guang Yang et al.

COMPUTERIZED MEDICAL IMAGING AND GRAPHICS (2021)

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Article Computer Science, Artificial Intelligence

BS-Net: Learning COVID-19 pneumonia severity on a large chest X-ray dataset

Alberto Signoroni et al.

Summary: This study presents an end-to-end deep learning architecture for predicting the degree of lung compromise in COVID-19 patients on Chest X-ray images. The proposed semi-quantitative scoring system shows significant prognostic value and outperforms human annotators. The BS-Net demonstrates high accuracy and self-attentive behavior, showcasing its potential for computer-assisted monitoring in clinical settings.

MEDICAL IMAGE ANALYSIS (2021)

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Article Computer Science, Artificial Intelligence

Detection of COVID-19 from speech signal using bio-inspired based cepstral features

Tusar Kanti Dash et al.

Summary: Early detection of COVID-19 is challenging due to its spreading nature and fear among people. Speech-based detection, focusing on coughing sounds, can improve efficiency. A new feature called COVID-19 Coefficient (C-19CC) is developed in this study for improved detection performance.

PATTERN RECOGNITION (2021)

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Article Environmental Sciences

Computational Intelligence-Based Model for Mortality Rate Prediction in COVID-19 Patients

Irfan Ullah Khan et al.

Summary: This study utilized ML algorithms and DL models to predict the mortality rate in COVID-19 cases, with the DL model performing the best with an accuracy of 0.97, demonstrating its significance over the baseline study in the literature.

INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH (2021)

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Article Computer Science, Information Systems

Adversarial Examples-Security Threats to COVID-19 Deep Learning Systems in Medical IoT Devices

Md Abdur Rahman et al.

Summary: Medical IoT devices are being integrated into pandemic management systems like COVID-19, with researchers using deep learning algorithms to identify COVID-19 phenomena. However, these DL algorithms have security vulnerabilities to adversarial perturbations, making DL models vulnerable to attacks without defensive mechanisms.

IEEE INTERNET OF THINGS JOURNAL (2021)

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Review Computer Science, Information Systems

Sonographic Diagnosis of COVID-19: A Review of Image Processing for Lung Ultrasound

Conor McDermott et al.

Summary: The increasing cases of COVID-19 worldwide highlight the need for tools to aid in early diagnosis and monitoring of patients. Lung ultrasound examination has been shown to be effective in detecting COVID-19 manifestations and is suited for routine use due to its portable and disinfectable nature. Challenges still remain with image interpretation, but the use of lung ultrasound imaging shows promise in diagnosing and monitoring COVID-19 cases.

FRONTIERS IN BIG DATA (2021)

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Article Immunology

Relationship Between the ABO Blood Group and the Coronavirus Disease 2019 (COVID-19) Susceptibility

Jiao Zhao et al.

Summary: There is a relationship between ABO blood group and susceptibility to COVID-19, with people with blood group A having an increased risk of infection and those with blood group O having a decreased risk.

CLINICAL INFECTIOUS DISEASES (2021)

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Article Health Care Sciences & Services

Automatic COVID-19 disease diagnosis using 1D convolutional neural network and augmentation with human respiratory sound based on parameters: cough, breath, and voice

Kranthi Kumar Lella et al.

Summary: By using a one-dimensional CNN model and an augmentation-based mechanism, the preprocessing performance of the COVID-19 sounds dataset was improved, leading to an automated diagnosis of COVID-19 disease.

AIMS PUBLIC HEALTH (2021)

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Review Endocrinology & Metabolism

COVID-19 and diabetes mellitus: from pathophysiology to clinical management

Soo Lim et al.

Summary: Initial studies have shown that patients with diabetes mellitus have a higher risk of severe COVID-19, potentially due to hyperglycaemia affecting immune and inflammatory responses. Further investigation is needed to determine the optimal management for patients with diabetes mellitus during the ongoing pandemic.

NATURE REVIEWS ENDOCRINOLOGY (2021)

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Review Nanoscience & Nanotechnology

An Overview on SARS-CoV-2 (COVID-19) and Other Human Coronaviruses and Their Detection Capability via Amplification Assay, Chemical Sensing, Biosensing, Immunosensing, and Clinical Assays

Yasin Orooji et al.

Summary: The emergence of a novel zoonotic coronavirus has led to a need for rapid detection methods, but current technologies are expensive and not easily accessible for on-site testing, presenting a significant global challenge in the fight against COVID-19.

NANO-MICRO LETTERS (2021)

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Article Computer Science, Artificial Intelligence

JCS: An Explainable COVID-19 Diagnosis System by Joint Classification and Segmentation

Yu-Huan Wu et al.

Summary: This paper proposes a novel JCS system for real-time and explainable COVID-19 chest CT diagnosis, trained on a large COVID-CS dataset. The system achieves efficient classification and segmentation results with high sensitivity and specificity for COVID-19 patients.

IEEE TRANSACTIONS ON IMAGE PROCESSING (2021)

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Article Radiology, Nuclear Medicine & Medical Imaging

Feature Enhancement in Medical Ultrasound Videos Using Contrast-Limited Adaptive Histogram Equalization

Prerna Singh et al.

JOURNAL OF DIGITAL IMAGING (2020)

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Article Biochemistry & Molecular Biology

MathDL: mathematical deep learning for D3R Grand Challenge 4

Duc Duy Nguyen et al.

JOURNAL OF COMPUTER-AIDED MOLECULAR DESIGN (2020)

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Editorial Material Public, Environmental & Occupational Health

Data sharing for novel coronavirus (COVID-19)

Vasee Moorthy et al.

BULLETIN OF THE WORLD HEALTH ORGANIZATION (2020)

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Article Biology

Computers and viral diseases. Preliminary bioinformatics studies on the design of a synthetic vaccine and a preventative peptidomimetic antagonist against the SARS-CoV-2 (2019-nCoV, COVID-19) coronavirus

B. Robson

COMPUTERS IN BIOLOGY AND MEDICINE (2020)

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Letter Medicine, General & Internal

Baricitinib as potential treatment for 2019-nCoV acute respiratory disease

Peter Richardson et al.

LANCET (2020)

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Article Medicine, General & Internal

A familial cluster of pneumonia associated with the 2019 novel coronavirus indicating person-to-person transmission: a study of a family cluster

Jasper Fuk-Woo Chan et al.

LANCET (2020)

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Letter Infectious Diseases

An interactive web-based dashboard to track COVID-19 in real time

Ensheng Dong et al.

LANCET INFECTIOUS DISEASES (2020)

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Open access epidemiological data from the COVID-19 outbreak

Bo Xu et al.

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Improved protein structure prediction using potentials from deep learning

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NATURE (2020)

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Article Radiology, Nuclear Medicine & Medical Imaging

Chest CT Findings in Coronavirus Disease 2019 (COVID-19): Relationship to Duration of Infection

Adam Bernheim et al.

RADIOLOGY (2020)

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Article Medicine, General & Internal

Assessing the Impact of Reduced Travel on Exportation Dynamics of Novel Coronavirus Infection (COVID-19)

Asami Anzai et al.

JOURNAL OF CLINICAL MEDICINE (2020)

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Article Medicine, General & Internal

Risk Assessment of Novel Coronavirus COVID-19 Outbreaks Outside China

Peter Boldog et al.

JOURNAL OF CLINICAL MEDICINE (2020)

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Article Anesthesiology

Coronaviruses and SARS-CoV-2: A Brief Overview

Stephan Ludwig et al.

ANESTHESIA AND ANALGESIA (2020)

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Review Anesthesiology

Application of Lung Ultrasound During the COVID-19 Pandemic: A Narrative Review

David L. Convissar et al.

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Article Biochemistry & Molecular Biology

Clinically Applicable AI System for Accurate Diagnosis, Quantitative Measurements, and Prognosis of COVID-19 Pneumonia Using Computed Tomography

Kang Zhang et al.

CELL (2020)

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Article Radiology, Nuclear Medicine & Medical Imaging

Any unique image biomarkers associated with COVID-19?

Jiantao Pu et al.

EUROPEAN RADIOLOGY (2020)

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Article Respiratory System

A fully automatic deep learning system for COVID-19 diagnostic and prognostic analysis

Shuo Wang et al.

EUROPEAN RESPIRATORY JOURNAL (2020)

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Article Infectious Diseases

A mathematical model for simulating the phase-based transmissibility of a novel coronavirus

Tian-Mu Chen et al.

INFECTIOUS DISEASES OF POVERTY (2020)

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Article Infectious Diseases

Public awareness, news promptness and the measles outbreak in Hong Kong from March to April, 2019

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