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Medmamba: Vision mamba for medical image classification
Y Yue, Z Li - arxiv preprint arxiv:2403.03849, 2024 - arxiv.org
Since the era of deep learning, convolutional neural networks (CNNs) and vision
transformers (ViTs) have been extensively studied and widely used in medical image …
transformers (ViTs) have been extensively studied and widely used in medical image …
[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 …
DeepChestGNN: A comprehensive framework for enhanced lung disease identification through advanced graphical deep features
Lung diseases are the third-leading cause of mortality in the world. Due to compromised
lung function, respiratory difficulties, and physiological complications, lung disease brought …
lung function, respiratory difficulties, and physiological complications, lung disease brought …
Explainable COVID-19 detection based on chest x-rays using an end-to-end RegNet architecture
M Chetoui, MA Akhloufi, EM Bouattane, J Abdulnour… - Viruses, 2023 - mdpi.com
COVID-19, which is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-
CoV-2), is one of the worst pandemics in recent history. The identification of patients …
CoV-2), is one of the worst pandemics in recent history. The identification of patients …
ResNet-50 vs. EfficientNet-B0: Multi-Centric Classification of Various Lung Abnormalities Using Deep Learning" Session id: ICMLDsE. 004"
K Kansal, TB Chandra, A Singh - Procedia Computer Science, 2024 - Elsevier
Lung abnormalities are among the significant contributors to morbidity and mortality
worldwide. It induces symptoms like coughing, sneezing, fever, breathlessness, etc., which …
worldwide. It induces symptoms like coughing, sneezing, fever, breathlessness, etc., which …
Feature selection of pre-trained shallow CNN using the QLESCA optimizer: COVID-19 detection as a case study
Abstract According to the World Health Organization, millions of infections and a lot of
deaths have been recorded worldwide since the emergence of the coronavirus disease …
deaths have been recorded worldwide since the emergence of the coronavirus disease …
[HTML][HTML] Multi-level training and testing of CNN models in diagnosing multi-center COVID-19 and pneumonia X-ray images
Featured Application Despite their reported high accuracy, a significant limitation of current
AI-assisted COVID-19 diagnostic models is that they are often trained on datasets sourced …
AI-assisted COVID-19 diagnostic models is that they are often trained on datasets sourced …
[HTML][HTML] Concatenated CNN-Based Pneumonia Detection Using a Fuzzy-Enhanced Dataset
AS Buriboev, D Muhamediyeva, H Primova, D Sultanov… - Sensors, 2024 - mdpi.com
Pneumonia is a form of acute respiratory infection affecting the lungs. Symptoms of viral and
bacterial pneumonia are similar. Rapid diagnosis of the disease is difficult, since …
bacterial pneumonia are similar. Rapid diagnosis of the disease is difficult, since …
A classification algorithm based on improved meta learning and transfer learning for few‐shot medical images
B Zhang, B Gao, S Liang, X Li, H Wang - IET Image Processing, 2023 - Wiley Online Library
At present, medical image classification algorithm plays an important role in clinical
diagnosis. However, due to the scarcity of data labels, small sample size, uneven …
diagnosis. However, due to the scarcity of data labels, small sample size, uneven …
Covid19-ResCapsNet: a novel residual capsule network for COVID-19 detection from chest X-ray scans images
Z Li, Q **ng, J Zhao, Y Miao, K Zhang, G Feng… - IEEE …, 2023 - ieeexplore.ieee.org
In the global outbreak of corona-virus disease (COVID-19), it is of foremost priority to find an
efficient and faster diagnosis method to reduce the transmission rate of the COVID-19 …
efficient and faster diagnosis method to reduce the transmission rate of the COVID-19 …