Medmamba: Vision mamba for medical image classification

Y Yue, Z Li - arXiv preprint arXiv:2403.03849, 2024 - arxiv.org
Medical image classification is a very fundamental and crucial task in the field of computer
vision. These years, CNN-based and Transformer-based models are widely used in …

[HTML][HTML] 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 …

[HTML][HTML] Feature selection of pre-trained shallow CNN using the QLESCA optimizer: COVID-19 detection as a case study

QS Hamad, H Samma, SA Suandi - Applied Intelligence, 2023 - Springer
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 …

[HTML][HTML] Multi-level training and testing of CNN models in diagnosing multi-center COVID-19 and pneumonia X-ray images

M Talaat, X Si, J Xi - Applied Sciences, 2023 - mdpi.com
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 …

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 …

[HTML][HTML] DeepChestGNN: A Comprehensive Framework for Enhanced Lung Disease Identification through Advanced Graphical Deep Features

S Rana, MJ Hosen, TJ Tonni, MAH Rony, K Fatema… - Sensors, 2024 - mdpi.com
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 …

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 …

M-HEALTH system for detecting COVID-19 in chest X-Rays using deep learning and data security approaches

J Delgado, L Clavijo, C Soria, J Ortega… - … Congress on Information …, 2023 - Springer
Advances in predicting different types of pathologies in medical images have been
significant in the last decade, thanks to the performance and efficiency of models trained …

COVID19-ResCapsNet: A Novel Residual Capsule Network for COVID-19 Detection From Chest X-Ray Scans Images

Z Li, Q Xing, 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 …

Detecting Lumpy Skin Disease Using Deep Learning Techniques

S Sambyal, S Kumar, S Shastri… - … Data Processing and …, 2023 - taylorfrancis.com
Lumpy skin disease (LSD), which has recently hit Asian countries, is an economically
devastating disease spreading in cattle. LSD results in the death of cattle on a large scale …