Proceedings ArticleDOI
COVID-19 Diagnosis Systems Based on Deep Convolutional Neural Networks Techniques: A Review
Hivi Ismat Dino,Subhi R. M. Zeebaree,Dathar Abas Hasan,Maiwan B. Abdulrazzaq,Lailan M. Haji,Hanan M. Shukur +5 more
- pp 184-189
TLDR
In this article, a deep convolutional neural network (DCNN) is used to extract valuable information by analyzing a massive amount of CXR and CT images that can critically impact on screening of Covid-19 cases.Abstract:
The rapidly spreading of the viral disease “COVID-19” causes millions of infections and deaths worldwide. It causes a devastating impact on the lifestyle, public health, and the global economy. This motivates the researchers to invent and develop innovative and automated methods to detect COVID-19 at its early stages. It is necessary to isolate the positive cases quickly to prevent this epidemic and treat affected patients. Many diagnosis methods are proposed to perform accurate and fast detection for COVID-19, such as Reverse Transcription-Polymerase Chain Reaction (RT -PCR). The clinical studies indicate that the severity of COVID-19 cases depends on the virus's amount within infected lungs. Chest X-ray (CXR) and Computed Tomography (CT) images are useful imaging methods for diagnosing COVID-19 cases. Deep Convolutional Neural Network (DCNN) is a machine learning technique usually used in computer vision applications. This review focuses on utilizing the DCNN methods for building an automated Computer-Aided Diagnosis (CADs) system to detect and classify the infected cases of the COVID-19 disease accurately and fast. These techniques are used to extracts valuable information by analyzing a massive amount of CXR and CT images that can critically impact on screening of Covid-19. DCNN techniques proved their robustness, potentiality, and advancement by comparing them among the other learning algorithms. It is worth noting that DCNN is an essential tool for supporting the physicians' clinical decisions.read more
Citations
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Journal ArticleDOI
Application of Machine Learning and Deep Learning Techniques for COVID-19 Screening Using Radiological Imaging: A Comprehensive Review
TL;DR: A comprehensive review has been conducted to summarize the works related to applications of AI/ML/DL for diagnostic prediction of COVID-19, mainly using X-ray and CT images as mentioned in this paper .
Proceedings ArticleDOI
Detection of COVID-19 using CNN's Deep Learning Method: Review
TL;DR: In this paper , a multi-layered CNN model was used to detect COVID-19 using 3.990 X-ray images and offers good accuracy, sensitivity, and specificity.
Proceedings ArticleDOI
Deep CNN and LSTM Architecture-Based Approach for COVID-19 Detection
TL;DR: In this paper , a CNN + LSTM model was proposed to detect the severe acute respiratory syndrome (SARS-CoV2) leading to a pandemic of respiratory disease, namely COVID19.
Proceedings ArticleDOI
Detection of COVID-19 using CNN's Deep Learning Method: Review
TL;DR: In this paper , a multi-layered CNN model was used to detect COVID-19 using 3.990 X-ray images and offers good accuracy, sensitivity, and specificity.
References
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