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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 …
[HTML][HTML] Deep learning for pneumonia detection in chest x-ray images: A comprehensive survey
This paper addresses the significant problem of identifying the relevant background and
contextual literature related to deep learning (DL) as an evolving technology in order to …
contextual literature related to deep learning (DL) as an evolving technology in order to …
Enhancing computer-aided cervical cancer detection using a novel fuzzy rank-based fusion
Cervical cancer is a severe and pervasive disease that poses a significant health threat to
women globally. The Pap smear test is an efficient and effective method for detecting …
women globally. The Pap smear test is an efficient and effective method for detecting …
A multistage framework for respiratory disease detection and assessing severity in chest X-ray images
Chest Radiography is a non-invasive imaging modality for diagnosing and managing
chronic lung disorders, encompassing conditions such as pneumonia, tuberculosis, and …
chronic lung disorders, encompassing conditions such as pneumonia, tuberculosis, and …
COVID-19 detection from Chest X-ray images using a novel lightweight hybrid CNN architecture
The pandemic of COVID-19 has affected worldwide population. Diagnosing this highly
contagious disease at an initial stage is essential for controlling its spread. In this paper, we …
contagious disease at an initial stage is essential for controlling its spread. In this paper, we …
Fedmrl: Data heterogeneity aware federated multi-agent deep reinforcement learning for medical imaging
Despite recent advancements in Federated Learning (FL) for medical image diagnosis,
addressing data heterogeneity among clients remains a significant challenge for practical …
addressing data heterogeneity among clients remains a significant challenge for practical …
Chaotic satin bowerbird optimizer based advanced AI techniques for detection of COVID-19 diseases from CT scans images
Abstract Background The SARS-CoV-2 virus, which caused the COVID-19 pandemic,
emerged in late 2019, leading to significant global health challenges due to the lack of …
emerged in late 2019, leading to significant global health challenges due to the lack of …
Interpretable COVID-19 chest X-ray detection based on handcrafted feature analysis and sequential neural network
Deep learning methods have significantly improved medical image analysis, particularly in
detecting COVID-19 chest X-rays. Nonetheless, these methodologies frequently inhibit some …
detecting COVID-19 chest X-rays. Nonetheless, these methodologies frequently inhibit some …
A high-accuracy lightweight network model for X-ray image diagnosis: A case study of COVID detection
S Wang, J Ren, X Guo - Plos one, 2024 - journals.plos.org
The Coronavirus Disease 2019 (COVID-19) has caused widespread and significant harm
globally. In order to address the urgent demand for a rapid and reliable diagnostic approach …
globally. In order to address the urgent demand for a rapid and reliable diagnostic approach …
Detection of Severe Lung Infection on Chest Radiographs of COVID-19 Patients: Robustness of AI Models across Multi-Institutional Data
The diagnosis of severe COVID-19 lung infection is important because it carries a higher risk
for the patient and requires prompt treatment with oxygen therapy and hospitalization while …
for the patient and requires prompt treatment with oxygen therapy and hospitalization while …