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Review of Artificial Intelligence Techniques in Imaging Data Acquisition, Segmentation and Diagnosis for COVID-19
The pandemic of coronavirus disease 2019 (COVID-19) is spreading all ove...
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Deep Learning in Detection and Diagnosis of Covid-19 using Radiology Modalities: A Systematic Review
Purpose: Early detection and diagnosis of Covid-19 and accurate separati...
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Automated Methods for Detection and Classification Pneumonia based on X-Ray Images Using Deep Learning
Recently, researchers, specialists, and companies around the world are r...
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Survey of the Detection and Classification of Pulmonary Lesions via CT and X-Ray
In recent years, the prevalence of several pulmonary diseases, especiall...
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A Review of Automatically Diagnosing COVID-19 based on Scanning Image
The pandemic of COVID-19 has caused millions of infectious. Due to the f...
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COVID-19 in differential diagnosis of online symptom assessments
The COVID-19 pandemic has magnified an already existing trend of people ...
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Epileptic seizure detection using deep learning techniques: A Review
A variety of screening approaches have been proposed to diagnose epilept...
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A Review on Deep Learning Techniques for the Diagnosis of Novel Coronavirus (COVID-19)
Novel coronavirus (COVID-19) outbreak, has raised a calamitous situation all over the world and has become one of the most acute and severe ailments in the past hundred years. The prevalence rate of COVID-19 is rapidly rising every day throughout the globe. Although no vaccines for this pandemic have been discovered yet, deep learning techniques proved themselves to be a powerful tool in the arsenal used by clinicians for the automatic diagnosis of COVID-19. This paper aims to overview the recently developed systems based on deep learning techniques using different medical imaging modalities like Computer Tomography (CT) and X-ray. This review specifically discusses the systems developed for COVID-19 diagnosis using deep learning techniques and provides insights on well-known data sets used to train these networks. It also highlights the data partitioning techniques and various performance measures developed by researchers in this field. A taxonomy is drawn to categorize the recent works for proper insight. Finally, we conclude by addressing the challenges associated with the use of deep learning methods for COVID-19 detection and probable future trends in this research area. This paper is intended to provide experts (medical or otherwise) and technicians with new insights into the ways deep learning techniques are used in this regard and how they potentially further works in combatting the outbreak of COVID-19.
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