Cov-Fed: Federated learning-based framework for COVID-19 diagnosis using chest X-ray scans
Abstract SARS-CoV-2, a member of the coronavirus family, causes COVID-19, which can
range from the ordinary cold to the rare but fatal Severe Acute Respiratory Syndrome …
range from the ordinary cold to the rare but fatal Severe Acute Respiratory Syndrome …
A systematic review of multilabel chest X-ray classification using deep learning
Chest X-ray scans are one of the most often used diagnostic tools for identifying chest
diseases. However, identifying diseases in X-ray images needs experienced technicians …
diseases. However, identifying diseases in X-ray images needs experienced technicians …
Label correlation guided discriminative label feature learning for multi-label chest image classification
Abstract Background and Objective Multi-label Chest X-ray (CXR) images often contain rich
label relationship information, which is beneficial to improve classification performance …
label relationship information, which is beneficial to improve classification performance …
Breast cancer prediction using Shapely and Game theory in Federated Learning environment
Y Supriya, R Chengoden - IEEE Access, 2024 - ieeexplore.ieee.org
Breast cancer is a critical health issue affecting the well-being of women. Breast cancer is
one of the most common causes of the increase in the mortality rate of women around the …
one of the most common causes of the increase in the mortality rate of women around the …
Ensemble federated learning for non-ii d covid-19 detection
In light of the COVID-19 pandemic, the need for a chest X-ray scans classifier is crucial in
order to diagnose patients and classify scans into normal, COVID-infected, and pneumonia …
order to diagnose patients and classify scans into normal, COVID-infected, and pneumonia …
Using deep neural network approach for multiple-class assessment of digital mammography
SY Hsu, CY Wang, YK Kao, KY Liu, MC Lin, LR Yeh… - Healthcare, 2022 - mdpi.com
According to the Health Promotion Administration in the Ministry of Health and Welfare
statistics in Taiwan, over ten thousand women have breast cancer every year …
statistics in Taiwan, over ten thousand women have breast cancer every year …
CorLabelNet: a comprehensive framework for multi-label chest X-ray image classification with correlation guided discriminant feature learning and oversampling
Recent advancements in deep learning techniques have significantly improved multi-label
chest X-ray (CXR) image classification for clinical diagnosis. However, most previous …
chest X-ray (CXR) image classification for clinical diagnosis. However, most previous …
Towards good practice for convolution and attention with PANs in federated medical image classification
In the current healthcare landscape, accurately diagnosing patients with respiratory
conditions while preserving data privacy has become a critical global concern. To address …
conditions while preserving data privacy has become a critical global concern. To address …
Multi-Label Classification of Lung Diseases Using Deep Learning
Assistance for doctors in disease detection can be very useful in environments with scarce
resources and personnel. Historically, many patients could have been cured with early …
resources and personnel. Historically, many patients could have been cured with early …
Federated two-stage decoupling with adaptive personalization layers
Federated learning has gained significant attention due to its groundbreaking ability to
enable distributed learning while maintaining privacy constraints. However, as a …
enable distributed learning while maintaining privacy constraints. However, as a …