A Robust Framework for Epidemic Analysis, Prediction and Detection of COVID-19

Article Instruments & Instrumentation

AI-driven deep convolutional neural networks for chest X-ray pathology identification

Saleh Albahli et al.

Summary: This study develops convolution neural network models to classify different chest diseases based on chest X-ray images. The use of data augmentation and generative adversarial network improves the accuracy of the classification.

JOURNAL OF X-RAY SCIENCE AND TECHNOLOGY (2022)

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Review Dentistry, Oral Surgery & Medicine

Coronavirus disease 2019 (COVID-19) vaccines: A concise review

Lakshman Perera Samaranayake et al.

Summary: The successful development of a vaccine against COVID-19 within a short period of time is a testament to human ingenuity, with vaccination being crucial for dental professionals as it may become a mandatory requirement in dental practice.

ORAL DISEASES (2022)

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Review Immunology

One Hundred Days of Coronavirus Disease 2019 Prevention and Control in China

Lei Zhou et al.

Summary: The article discusses the emergence of the novel coronavirus pandemic in China, detailing the country's response with two phases of containment strategy, key areas of focus, and future considerations. It also describes specific strategies used by China for risk assessment, resource prioritization, and public health interventions at different risk levels, as well as challenges faced in terms of societal involvement, logistics, and supply chains. Finally, the methods China is taking to cautiously restart social life and economic activity are outlined.

CLINICAL INFECTIOUS DISEASES (2021)

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Article Radiology, Nuclear Medicine & Medical Imaging

A Deep Neural Network to Distinguish COVID-19 from other Chest Diseases Using X-ray Images

Saleh Albahli

Summary: Detection of COVID-19 through lung scans requires a multidisciplinary approach for diagnosis confirmation. Limited works focus on pathological x-ray images, with challenges like data scarcity and imbalance impacting detection accuracy.

CURRENT MEDICAL IMAGING (2021)

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Article Computer Science, Artificial Intelligence

Classification of COVID-19 in chest X-ray images using DeTraC deep convolutional neural network

Asmaa Abbas et al.

Summary: This paper validates a deep CNN model called DeTraC, which utilizes a class decomposition mechanism to handle irregularities in medical image datasets. Experimental results demonstrate the high accuracy of DeTraC in detecting COVID-19 X-ray images.

APPLIED INTELLIGENCE (2021)

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Article Computer Science, Artificial Intelligence

Automated diagnosis of COVID-19 with limited posteroanterior chest X-ray images using fine-tuned deep neural networks

Narinder Singh Punn et al.

Summary: The novel coronavirus 2019 (COVID-19) presents a respiratory syndrome resembling pneumonia, with the current diagnostic procedure being less sensitive at the initial stage. To improve diagnosis efficiency, publicly available datasets of corona positive patients are being utilized for faster and automated diagnosis using deep learning approaches. Various state-of-the-art deep learning models are being fine-tuned using random oversampling and weighted class loss function techniques for improved classification of COVID-19 cases in chest X-ray images. NASNetLarge shows better performance compared to other architectures, as demonstrated through evaluation metrics such as accuracy, precision, recall, loss, and area under the curve (AUC).

APPLIED INTELLIGENCE (2021)

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Article Computer Science, Artificial Intelligence

Coronavirus disease (COVID-19) detection using X-ray images and enhanced DenseNet

Saleh Albahli et al.

Summary: The COVID-19 pandemic originating from China has spread rapidly worldwide, leading to over 104 million cases and 2 million deaths by the end of January. Due to the decrease in test kit availability, an automatic detection system is proposed as an alternative diagnostic method to prevent further spread. Three different BiT models were analyzed for diagnosing coronavirus pneumonia in chest X-ray radiographs, with the DenseNet model showing the highest classification efficiency at 92%.

APPLIED SOFT COMPUTING (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 Biology

An automated COVID-19 detection based on fused dynamic exemplar pyramid feature extraction and hybrid feature selection using deep learning

Fatih Ozyurt et al.

Summary: The proposed model introduces a novel technique for automatic detection of COVID-19 using CT images, achieving high classification accuracies through handcrafted feature generation and hybrid feature selection. Through preprocessing and advanced feature extraction methods, the model successfully identifies COVID-19 with ANN and DNN models reaching over 94% accuracy.

COMPUTERS IN BIOLOGY AND MEDICINE (2021)

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Article Health Care Sciences & Services

Deep Learning on Chest X-ray Images to Detect and Evaluate Pneumonia Cases at the Era of COVID-19

Karim Hammoudi et al.

Summary: COVID-19, initially presenting flu-like symptoms and causing pneumonia, has led to a global pandemic. This study explores the use of deep learning to automatically analyze chest X-ray images for screening and diagnosing COVID-19 patients.

JOURNAL OF MEDICAL SYSTEMS (2021)

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Article Computer Science, Information Systems

End-to-End Image Steganography Using Deep Convolutional Autoencoders

Nandhini Subramanian et al.

Summary: A new image steganography method is proposed in this study using a lightweight deep convolutional autoencoder architecture, which outperforms traditional methods in terms of hiding capacity, security, robustness, and imperceptibility.

IEEE ACCESS (2021)

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Article Computer Science, Information Systems

Deep Learning-Based COVID-19 Detection Using CT and X-Ray Images: Current Analytics and Comparisons

Amjad Rehman et al.

Summary: COVID-19 is a global challenge with millions infected and dead. Researchers are working on finding effective measures to combat the pandemic, and this article discusses using deep learning methods for COVID-19 detection and data analysis.

IT PROFESSIONAL (2021)

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Review Computer Science, Information Systems

Image Steganography: A Review of the Recent Advances

Nandhini Subramanian et al.

Summary: This paper introduces the concept of image steganography and the application of deep learning in this field, summarizing different types of deep learning methods and related datasets, experimental setups, and evaluation metrics. It aims to help researchers understand the current trends and challenges by providing information summaries and future directions.

IEEE ACCESS (2021)

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Article Computer Science, Artificial Intelligence

Deep learning in video multi-object tracking: A survey

Gioele Ciaparrone et al.

NEUROCOMPUTING (2020)

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Review Health Care Sciences & Services

Review of the Clinical Characteristics of Coronavirus Disease 2019 (COVID-19)

Fang Jiang et al.

JOURNAL OF GENERAL INTERNAL MEDICINE (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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Article Multidisciplinary Sciences

A new coronavirus associated with human respiratory disease in China

Fan Wu et al.

NATURE (2020)

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Article Engineering, Biomedical

Extracting Possibly Representative COVID-19 Biomarkers from X-ray Images with Deep Learning Approach and Image Data Related to Pulmonary Diseases

Ioannis D. Apostolopoulos et al.

JOURNAL OF MEDICAL AND BIOLOGICAL ENGINEERING (2020)

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Article Physics, Multidisciplinary

Mathematical prediction of the time evolution of the COVID-19 pandemic in Italy by a Gauss error function and Monte Carlo simulations

Ignazio Ciufolini et al.

EUROPEAN PHYSICAL JOURNAL PLUS (2020)

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Letter Infectious Diseases

Real estimates of mortality following COVID-19 infection

David Baud et al.

LANCET INFECTIOUS DISEASES (2020)

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Article Biology

CovXNet: A multi-dilation convolutional neural network for automatic COVID-19 and other pneumonia detection from chest X-ray images with transferable multi-receptive feature optimization

Tanvir Mahmud et al.

COMPUTERS IN BIOLOGY AND MEDICINE (2020)

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Article Biology

Automated detection of COVID-19 cases using deep neural networks with X-ray images

Tulin Ozturk et al.

COMPUTERS IN BIOLOGY AND MEDICINE (2020)

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Review Computer Science, Artificial Intelligence

COVID-CAPS: A capsule network-based framework for identification of COVID-19 cases from X-ray images

Parnian Afshar et al.

PATTERN RECOGNITION LETTERS (2020)

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Article Physics, Multidisciplinary

A Gaussian Model for the Time Development of the Sars-Cov-2 Corona Pandemic Disease. Predictions for Germany Made on 30 March 2020

Reinhard Schlickeiser et al.

PHYSICS (2020)

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Article Physics, Multidisciplinary

Covid-19 Predictions Using a Gauss Model, Based on Data from April 2

Janik Schuettler et al.

PHYSICS (2020)

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Article Multidisciplinary Sciences

COVID-Net: a tailored deep convolutional neural network design for detection of COVID-19 cases from chest X-ray images

Linda Wang et al.

SCIENTIFIC REPORTS (2020)

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Article Computer Science, Interdisciplinary Applications

CoroNet: A deep neural network for detection and diagnosis of COVID-19 from chest x-ray images

Asif Iqbal Khan et al.

COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE (2020)

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Article Engineering, Biomedical

Covid-19: automatic detection from X-ray images utilizing transfer learning with convolutional neural networks

Ioannis D. Apostolopoulos et al.

PHYSICAL AND ENGINEERING SCIENCES IN MEDICINE (2020)

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Article Computer Science, Information Systems

Can AI Help in Screening Viral and COVID-19 Pneumonia?

Muhammad E. H. Chowdhury et al.

IEEE ACCESS (2020)

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Article Computer Science, Artificial Intelligence

Differential convolutional neural network

M. Sarigul et al.

NEURAL NETWORKS (2019)

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Article Public, Environmental & Occupational Health

Comparative analysis of computer-vision and BLE technology based indoor navigation systems for people with visual impairments

Jayakanth Kunhoth et al.

INTERNATIONAL JOURNAL OF HEALTH GEOGRAPHICS (2019)

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Article Computer Science, Artificial Intelligence

Recent advances in convolutional neural networks

Jiuxiang Gu et al.

PATTERN RECOGNITION (2018)

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Proceedings Paper Computer Science, Artificial Intelligence

A survey on deep learning based approaches for action and gesture recognition in image sequences

Maryam Asadi-Aghbolaghi et al.

2017 12TH IEEE INTERNATIONAL CONFERENCE ON AUTOMATIC FACE AND GESTURE RECOGNITION (FG 2017) (2017)

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Article Physics, Fluids & Plasmas

Towards a complete parametrization of the ordinary-mode electromagnetic instability in counterstreaming plasmas. I. Minimizing ion dynamics

D. Ibscher et al.

PHYSICS OF PLASMAS (2013)

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A Robust Framework for Epidemic Analysis, Prediction and Detection of COVID-19

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