4.2 Review

X-Ray Equipped with Artificial Intelligence: Changing the COVID-19 Diagnostic Paradigm during the Pandemic

Related references

Note: Only part of the references are listed.
Article Computer Science, Information Systems

Covid-19 detection in chest X-ray through random forest classifier using a hybridization of deep CNN and DWT optimized features

Rafid Mostafiz et al.

Summary: This paper proposes an intelligent approach to detect Covid-19 from chest X-ray images by hybridizing deep CNN and DWT features. Experimental results demonstrate that the approach outperforms existing methods with an overall accuracy of over 98.5%.

JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES (2022)

Article Biochemistry & Molecular Biology

Using X-ray images and deep learning for automated detection of coronavirus disease

Khalid El Asnaoui et al.

Summary: The study compared the use of deep learning models for the detection and classification of coronavirus pneumonia, finding that Inception_ResNetV2 and DenseNet201 performed better than other models used in the research.

JOURNAL OF BIOMOLECULAR STRUCTURE & DYNAMICS (2021)

Article Computer Science, Artificial Intelligence

COVIDetectioNet: COVID-19 diagnosis system based on X-ray images using features selected from pre-learned deep features ensemble

Muammer Turkoglu

Summary: The novel coronavirus has spread rapidly worldwide, resulting in a global pandemic that has posed a significant threat to human health. The limitations and time constraints of COVID-19 diagnostic tests have led to the utilization of lung X-ray images as a faster and more reliable method for diagnosis. The proposed COVIDetectioNet model, utilizing deep features and machine learning techniques, has shown a high accuracy of 99.18% in diagnosing COVID-19 from X-ray images, outperforming previous studies.

APPLIED INTELLIGENCE (2021)

Article Computer Science, Artificial Intelligence

Deep learning based detection and analysis of COVID-19 on chest X-ray images

Rachna Jain et al.

Summary: Covid-19 is a rapidly spreading viral disease that affects both humans and animals. Deep learning techniques can provide useful analysis of chest x-ray images to aid in the screening of Covid-19. The Xception model shows the highest accuracy in detecting chest x-ray images compared to other models.

APPLIED INTELLIGENCE (2021)

Article Radiology, Nuclear Medicine & Medical Imaging

The sensitivity and specificity of chest CT in the diagnosis of COVID-19

Anita Kovacs et al.

Summary: This review examined the sensitivity, specificity, and feasibility of chest CT in detecting COVID-19 compared with RT-PCR. Results showed high sensitivity (67-100%) and relatively low specificity (25-80%) for CT scans, while RT-PCR had modest sensitivity (53-88%). A reverse calculation approach indicated that CT could have higher specificity (83-100%) if considering the modest sensitivity of RT-PCR. Arguments were presented for the added value of chest CT scans in diagnosing COVID-19, especially in patients with typical symptoms and negative RT-PCR results in highly infected regions.

EUROPEAN RADIOLOGY (2021)

Article Engineering, Electrical & Electronic

Classification of Coronavirus (COVID-19) fromX-rayandCTimages using shrunken features

Saban Ozturk et al.

Summary: The study highlights the importance of using machine learning methods to detect viral epidemics by analyzing X-ray and CT images for making an effective diagnosis of COVID-19. Utilizing shallow image augmentation and the Synthetic Minority Over-sampling Technique algorithm proved to be effective for handling deficient and unbalanced datasets in this research.

INTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY (2021)

Article Mathematics, Interdisciplinary Applications

CoroDet: A deep learning based classification for COVID-19 detection using chest X-ray images

Emtiaz Hussain et al.

Summary: A novel CNN model called CoroDet was proposed for automatic detection of COVID-19 using raw chest X-ray and CT scan images in this study. The model outperformed existing techniques in terms of classification accuracy, providing a solution to the issue of scarcity of COVID-19 testing kits.

CHAOS SOLITONS & FRACTALS (2021)

Article Engineering, Multidisciplinary

A hybrid deep transfer learning model with machine learning methods for face mask detection in the era of the COVID-19 pandemic

Mohamed Loey et al.

Summary: This paper introduces a hybrid model using deep and classical machine learning for face mask detection. The model consists of two components for feature extraction and mask classification, achieving high testing accuracy in different datasets.

MEASUREMENT (2021)

Article Computer Science, Artificial Intelligence

E-DiCoNet: Extreme learning machine based classifier for diagnosis of COVID-19 using deep convolutional network

R. Murugan et al.

Summary: The global spread of the COVID-19 pandemic has highlighted the need for automated diagnosis methods. By utilizing an improved CNN model, more accurate diagnosis of COVID-19 and other diseases can be achieved, helping to alleviate the burden on healthcare systems.

JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING (2021)

Article Computer Science, Artificial Intelligence

InstaCovNet-19: A deep learning classification model for the detection of COVID-19 patients using Chest X-ray

Anunay Gupta et al.

Summary: The newly discovered coronavirus (COVID-19) has caused a global pandemic, but artificial intelligence models play a significant role in medical diagnosis. The proposed model successfully detects COVID-19 and pneumonia with high accuracy, benefiting humanity greatly during this age of Quarantine.

APPLIED SOFT COMPUTING (2021)

Article Computer Science, Artificial Intelligence

COVID-19 X-ray images classification based on enhanced fractional-order cuckoo search optimizer using heavy-tailed distributions

Dalia Yousri et al.

Summary: This study proposes an alternative method for classifying COVID-19 X-ray images by extracting informative features and using a new feature selection method, leveraging an enhanced cuckoo search optimization algorithm and four different heavy-tailed distributions. Experimental results show that the method can provide accurate results for both UCI and COVID-19 datasets.

APPLIED SOFT COMPUTING (2021)

Article Computer Science, Artificial Intelligence

Coronavirus disease (COVID-19) detection in Chest X-Ray images using majority voting based classifier ensemble

Tej Bahadur Chandra et al.

Summary: This study introduces an automatic COVID screening (ACoS) system for identifying nCOVID-19 infected patients, which utilizes radiomic texture descriptors and a majority vote based classifier ensemble of five benchmark supervised classification algorithms. The system shows promising performance in the validation phase, with statistically significant results confirmed through Friedman post-hoc multiple comparisons and z-test statistics.

EXPERT SYSTEMS WITH APPLICATIONS (2021)

Article Computer Science, Information Systems

A new approach for classifying coronavirus COVID-19 based on its manifestation on chest X-rays using texture features and neural networks

Sergio Varela-Santos et al.

Summary: In this study, supervised learning models were used to conduct experiments in accurately classifying medical images of COVID-19 patients and other related lung diseases. The goal was to lay the groundwork for the future development of a system capable of automatically detecting the COVID-19 disease based on its manifestation on chest X-rays and computerized tomography images of the lungs.

INFORMATION SCIENCES (2021)

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)

Article Computer Science, Artificial Intelligence

SuFMoFPA: A superpixel and meta-heuristic based fuzzy image segmentation approach to explicate COVID-19 radiological images

Shouvik Chakraborty et al.

Summary: COVID-19 is a major challenge for mankind, with researchers still working to find a vaccine or treatment. The virus is highly infectious, making it a global threat, but precautions like testing and preventative measures can help control its spread.

EXPERT SYSTEMS WITH APPLICATIONS (2021)

Article Health Care Sciences & Services

Deep Convolutional Neural Network-Based Computer-Aided Detection System for COVID-19 Using Multiple Lung Scans: Design and Implementation Study

Mustafa Ghaderzadeh et al.

Summary: A highly efficient computer-aided detection (CAD) system using a neural search architecture network (NASNet)-based algorithm was designed for COVID-19 detection, achieving remarkable results in identifying patients with COVID-19 in the early stages. The performance of the CAD system demonstrated high detection sensitivity, specificity, and accuracy, showing potential to help radiologists detect COVID-19 early on and prevent the loss of healthcare resources during the pandemic.

JOURNAL OF MEDICAL INTERNET RESEARCH (2021)

Article Multidisciplinary Sciences

COVID-Classifier: an automated machine learning model to assist in the diagnosis of COVID-19 infection in chest X-ray images

Abolfazl Zargari Khuzani et al.

Summary: The study explores the use of machine learning classifiers to differentiate COVID-19 from other pneumonia cases based on CXR images, suggesting that it can be a valuable tool for rapid triage and diagnosis.

SCIENTIFIC REPORTS (2021)

Review Health Care Sciences & Services

Deep Learning in the Detection and Diagnosis of COVID-19 Using Radiology Modalities: A Systematic Review

Mustafa Ghaderzadeh et al.

Summary: This systematic review provides an overview of the current state of radiology modalities for the detection and diagnosis of COVID-19 through deep learning, showing that these models have the ability to offer an accurate and efficient system, leading to a significant increase in sensitivity and specificity values.

JOURNAL OF HEALTHCARE ENGINEERING (2021)

Article Computer Science, Artificial Intelligence

Automatic COVID-19 lung infected region segmentation and measurement using CT-scans images

Adel Oulefki et al.

Summary: The study aims to design and evaluate an automatic tool for automatic COVID-19 Lung Infection segmentation and measurement using chest CT images. Extensive computer simulations show better efficiency and flexibility of this end to end learning approach on CT image segmentation with image enhancement, comparing to state of the art segmentation approaches like GraphCut, Medical Image Segmentation (MIS), and Watershed.

PATTERN RECOGNITION (2021)

Review Computer Science, Software Engineering

Machine Learning in Detection and Classification of Leukemia Using Smear Blood Images: A Systematic Review

Mustafa Ghaderzadeh et al.

Summary: Using machine learning techniques to process leukemia smear images can significantly improve accuracy and efficiency in leukemia detection and classification, with deep learning showing promise in achieving high precision. In addition to enhancing diagnostic services, ML methods offer faster, cheaper, and safer alternatives to traditional diagnosis methods, attracting attention from both the medical and AI communities.

SCIENTIFIC PROGRAMMING (2021)

Article Automation & Control Systems

Automatic Detection of COVID-19 Infection Using Chest X-Ray Images Through Transfer Learning

Elene Firmeza Ohata et al.

Summary: The new coronavirus has become a global pandemic, infecting over 1 million people and causing more than 50 thousand deaths. A new method for automatically detecting COVID-19 infection based on chest X-ray images has been proposed and shown to be efficient in detecting COVID-19 in X-ray images.

IEEE-CAA JOURNAL OF AUTOMATICA SINICA (2021)

Article Medicine, General & Internal

Clinical Characteristics of 138 Hospitalized Patients With 2019 Novel Coronavirus-Infected Pneumonia in Wuhan, China

Dawei Wang et al.

JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION (2020)

Article Radiology, Nuclear Medicine & Medical Imaging

Clinical Features and Chest CT Manifestations of Coronavirus Disease 2019 (COVID-19) in a Single-Center Study in Shanghai, China

Zenghui Cheng et al.

AMERICAN JOURNAL OF ROENTGENOLOGY (2020)

Article Mathematics, Interdisciplinary Applications

Application of deep learning for fast detection of COVID-19 in X-Rays using nCOVnet

Harsh Panwar et al.

CHAOS SOLITONS & FRACTALS (2020)

Article Orthopedics

Deep learning COVID-19 detection bias: accuracy through artificial intelligence

Shashank Vaid et al.

INTERNATIONAL ORTHOPAEDICS (2020)

Letter Medicine, General & Internal

Detection of SARS-CoV-2 in Different Types of Clinical Specimens

Wenling Wang et al.

JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION (2020)

Article Radiology, Nuclear Medicine & Medical Imaging

Diagnostic performance of chest CT to differentiate COVID-19 pneumonia in non-high-epidemic area in Japan

Yuki Himoto et al.

JAPANESE JOURNAL OF RADIOLOGY (2020)

Article Orthopedics

Using Machine Learning to Estimate Unobserved COVID-19 Infections in North America

Shashank Vaid et al.

JOURNAL OF BONE AND JOINT SURGERY-AMERICAN VOLUME (2020)

Article Radiology, Nuclear Medicine & Medical Imaging

Chest CT Features of COVID-19 in Rome, Italy

Damiano Caruso et al.

RADIOLOGY (2020)

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)

Article Radiology, Nuclear Medicine & Medical Imaging

Generalizability of Deep Learning Tuberculosis Classifier to COVID-19 Chest Radiographs New Tricks for an Old Algorithm?

Paul H. Yi et al.

JOURNAL OF THORACIC IMAGING (2020)

Article Medicine, General & Internal

Presymptomatic SARS-CoV-2 Infections and Transmission in a Skilled Nursing Facility

M. M. Arons et al.

NEW ENGLAND JOURNAL OF MEDICINE (2020)

Article Medicine, General & Internal

Weakly Labeled Data Augmentation for Deep Learning: A Study on COVID-19 Detection in Chest X-Rays

Sivaramakrishnan Rajaraman et al.

DIAGNOSTICS (2020)

Article Automation & Control Systems

An automated Residual Exemplar Local Binary Pattern and iterative ReliefF based COVID-19 detection method using chest X-ray image

Turker Tuncer et al.

CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS (2020)

Review Radiology, Nuclear Medicine & Medical Imaging

Portable chest X-ray in coronavirus disease-19 (COVID-19): A pictorial review

Adam Jacobi et al.

CLINICAL IMAGING (2020)

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)

Article Computer Science, Interdisciplinary Applications

A Weakly-Supervised Framework for COVID-19 Classification and Lesion Localization From Chest CT

Xinggang Wang et al.

IEEE TRANSACTIONS ON MEDICAL IMAGING (2020)

Article Computer Science, Interdisciplinary Applications

Inf-Net: Automatic COVID-19 Lung Infection Segmentation From CT Images

Deng-Ping Fan et al.

IEEE TRANSACTIONS ON MEDICAL IMAGING (2020)

Article Engineering, Multidisciplinary

A Deep Learning System to Screen Novel Coronavirus Disease 2019 Pneumonia

Xiaowei Xu et al.

ENGINEERING (2020)

Article Engineering, Biomedical

Computer-aided detection of COVID-19 from X-ray images using multi-CNN and Bayesnet classifier

Bejoy Abraham et al.

BIOCYBERNETICS AND BIOMEDICAL ENGINEERING (2020)

Article Engineering, Biomedical

A deep learning approach to detect Covid-19 coronavirus with X-Ray images

Govardhan Jain et al.

BIOCYBERNETICS AND BIOMEDICAL ENGINEERING (2020)

Article Computer Science, Interdisciplinary Applications

COVID-19 identification in chest X-ray images on flat and hierarchical classification scenarios

Rodolfo M. Pereira et al.

COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE (2020)

Article Multidisciplinary Sciences

New machine learning method for image-based diagnosis of COVID-19

Mohamed Abd Elaziz et al.

PLOS ONE (2020)

Article Radiology, Nuclear Medicine & Medical Imaging

Frequency and Distribution of Chest Radiographic Findings in Patients Positive for COVID-19

Ho Yuen Frank Wong et al.

RADIOLOGY (2020)

Article Instruments & Instrumentation

Identification of COVID-19 samples from chest X-Ray images using deep learning: A comparison of transfer learning approaches

Md Mamunur Rahaman et al.

JOURNAL OF X-RAY SCIENCE AND TECHNOLOGY (2020)

Article Computer Science, Artificial Intelligence

Deep-COVID: Predicting COVID-19 from chest X-ray images using deep transfer learning

Shervin Minaee et al.

MEDICAL IMAGE ANALYSIS (2020)

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)

Article Environmental Sciences

Unveiling COVID-19 from CHEST X-Ray with Deep Learning: A Hurdles Race with Small Data

Enzo Tartaglione et al.

INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH (2020)

Article Mathematical & Computational Biology

COVID19XrayNet: A Two-Step Transfer Learning Model for the COVID-19 Detecting Problem Based on a Limited Number of Chest X-Ray Images

Ruochi Zhang et al.

INTERDISCIPLINARY SCIENCES-COMPUTATIONAL LIFE SCIENCES (2020)

Article Computer Science, Artificial Intelligence

A multi-task pipeline with specialized streams for classification and segmentation of infection manifestations in COVID-19 scans

Shimaa El-bana et al.

PEERJ COMPUTER SCIENCE (2020)

Article Computer Science, Information Systems

Improving the performance of CNN to predict the likelihood of COVID-19 using chest X-ray images with preprocessing algorithms

Morteza Heidari et al.

INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS (2020)

Article Multidisciplinary Sciences

Optimised genetic algorithm-extreme learning machine approach for automatic COVID-19 detection

Musatafa Abbas Abbood Albadr et al.

PLOS ONE (2020)

Article Health Care Sciences & Services

Exploiting Multiple Optimizers with Transfer Learning Techniques for the Identification of COVID-19 Patients

Zeming Fan et al.

JOURNAL OF HEALTHCARE ENGINEERING (2020)

Article Computer Science, Information Systems

COVIDGR Dataset and COVID-SDNet Methodology for Predicting COVID-19 Based on Chest X-Ray Images

S. Tabik et al.

IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS (2020)

Article Multidisciplinary Sciences

Lung CT Segmentation to Identify Consolidations and Ground Glass Areas for Quantitative Assesment of SARS-CoV Pneumonia

Arrigo Cattabriga et al.

JOVE-JOURNAL OF VISUALIZED EXPERIMENTS (2020)

Article Medicine, General & Internal

Diagnostic accuracy of X-ray versus CT in COVID-19: a propensity-matched database study

Aditya Borakati et al.

BMJ OPEN (2020)

Article Engineering, Multidisciplinary

A Classification-Detection Approach of COVID-19 Based on Chest X-ray and CT by Using Keras Pre-Trained Deep Learning Models

Xing Deng et al.

CMES-COMPUTER MODELING IN ENGINEERING & SCIENCES (2020)

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)

Article Computer Science, Interdisciplinary Applications

Explainable Deep Learning for Pulmonary Disease and Coronavirus COVID-19 Detection from X-rays

Luca Brunese et al.

COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE (2020)

Article Medical Informatics

The investigation of multiresolution approaches for chest X-ray image based COVID-19 detection

Aras M. Ismael et al.

HEALTH INFORMATION SCIENCE AND SYSTEMS (2020)

Article Engineering, Biomedical

Truncated inception net: COVID-19 outbreak screening using chest X-rays

Dipayan Das et al.

PHYSICAL AND ENGINEERING SCIENCES IN MEDICINE (2020)

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)

Article Computer Science, Artificial Intelligence

COVID-19 Detection in Chest X-ray Images using a Deep Learning Approach

Fatima A. Saiz et al.

INTERNATIONAL JOURNAL OF INTERACTIVE MULTIMEDIA AND ARTIFICIAL INTELLIGENCE (2020)

Article Computer Science, Information Systems

On the Detection of COVID-19 from Chest X-Ray Images Using CNN-Based Transfer Learning

Mohammad Shorfuzzaman et al.

CMC-COMPUTERS MATERIALS & CONTINUA (2020)

Article Computer Science, Information Systems

CovidGAN: Data Augmentation Using Auxiliary Classifier GAN for Improved Covid-19 Detection

Abdul Waheed et al.

IEEE ACCESS (2020)

Article Computer Science, Information Systems

COVID-19 Detection Through Transfer Learning Using Multimodal Imaging Data

Michael J. Horry et al.

IEEE ACCESS (2020)

Article Computer Science, Theory & Methods

A survey on Image Data Augmentation for Deep Learning

Connor Shorten et al.

JOURNAL OF BIG DATA (2019)

Review Medicine, General & Internal

Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement

David Moher et al.

PLOS MEDICINE (2009)

Article Radiology, Nuclear Medicine & Medical Imaging

Optimizing parameters for computer-aided diagnosis of microcalcifications at mammography

I Leichter et al.

ACADEMIC RADIOLOGY (2000)