Automated detection and forecasting of covid-19 using deep learning techniques: A review
Abstract In March 2020, the World Health Organization (WHO) declared COVID-19 a global
epidemic, caused by the SARS-CoV-2 virus. Initially, COVID-19 was diagnosed using real …
epidemic, caused by the SARS-CoV-2 virus. Initially, COVID-19 was diagnosed using real …
Detection of Covid-19 and other pneumonia cases from CT and X-ray chest images using deep learning based on feature reuse residual block and depthwise dilated …
G Celik - Applied Soft Computing, 2023 - Elsevier
Covid-19 has become a worldwide epidemic which has caused the death of millions in a
very short time. This disease, which is transmitted rapidly, has mutated and different …
very short time. This disease, which is transmitted rapidly, has mutated and different …
[HTML][HTML] Applications of deep learning in disease diagnosis of chest radiographs: A survey on materials and methods
Recent advances in deep learning have given rise to high performance in image analysis
operations in healthcare. Lung diseases are of particular interest, as most can be identified …
operations in healthcare. Lung diseases are of particular interest, as most can be identified …
McS-Net: Multi-class Siamese network for severity of COVID-19 infection classification from lung CT scan slices
S Ahuja, BK Panigrahi, N Dey, A Taneja… - Applied Soft Computing, 2022 - Elsevier
Worldwide COVID-19 is a highly infectious and rapidly spreading disease in almost all age
groups. The Computed Tomography (CT) scans of lungs are found to be accurate for the …
groups. The Computed Tomography (CT) scans of lungs are found to be accurate for the …
COVID-19 diagnosis via chest X-ray image classification based on multiscale class residual attention
S Liu, T Cai, X Tang, Y Zhang, C Wang - Computers in Biology and …, 2022 - Elsevier
Aiming at detecting COVID-19 effectively, a multiscale class residual attention (MCRA)
network is proposed via chest X-ray (CXR) image classification. First, to overcome the data …
network is proposed via chest X-ray (CXR) image classification. First, to overcome the data …
[HTML][HTML] NSCGCN: A novel deep GCN model to diagnosis COVID-19
Abstract Aim Corona Virus Disease 2019 (COVID-19) was a lung disease with high mortality
and was highly contagious. Early diagnosis of COVID-19 and distinguishing it from …
and was highly contagious. Early diagnosis of COVID-19 and distinguishing it from …
Evaluating COVID-19 infection prevention measures in Malaysia: A fuzzy DEMATEL approach
E Yadegaridehkordi, M Nilashi… - Digital …, 2023 - journals.sagepub.com
Objective Since unexpected COVID-19 has been causing massive losses worldwide,
preventive measures have been emergency provided to curb the expansion of the epidemic …
preventive measures have been emergency provided to curb the expansion of the epidemic …
Applications of deep learning for drug discovery systems with bigdata
Y Matsuzaka, R Yashiro - BioMedInformatics, 2022 - mdpi.com
The adoption of “artificial intelligence (AI) in drug discovery”, where AI is used in the process
of pharmaceutical research and development, is progressing. By using the ability to process …
of pharmaceutical research and development, is progressing. By using the ability to process …
A review of deep learning imaging diagnostic methods for Covid-19
T Zhou, F Liu, H Lu, C Peng, X Ye - Electronics, 2023 - mdpi.com
COVID-19 (coronavirus disease 2019) is a new viral infection disease that is widely spread
worldwide. Deep learning plays an important role in COVID-19 images diagnosis. This …
worldwide. Deep learning plays an important role in COVID-19 images diagnosis. This …
[PDF][PDF] Tuberculosis detection in X-Ray image using deep learning approach with VGG-16 architecture
S Aulia, S Hadiyoso - Jurnal Ilmiah Teknik Elektro Komputer dan …, 2022 - eprints.uad.ac.id
Tuberculosis (TB) is a chronic disease still the main problem in Indonesia. However, this
disease can be cured with drugs at a particular time after the patient is detected as having …
disease can be cured with drugs at a particular time after the patient is detected as having …