Deep learning and medical image analysis for COVID-19 diagnosis and prediction
The coronavirus disease 2019 (COVID-19) pandemic has imposed dramatic challenges to
health-care organizations worldwide. To combat the global crisis, the use of thoracic …
health-care organizations worldwide. To combat the global crisis, the use of thoracic …
Federated learning for predicting clinical outcomes in patients with COVID-19
Federated learning (FL) is a method used for training artificial intelligence models with data
from multiple sources while maintaining data anonymity, thus removing many barriers to …
from multiple sources while maintaining data anonymity, thus removing many barriers to …
[HTML][HTML] Advances in artificial intelligence for accurate and timely diagnosis of COVID-19: A comprehensive review of medical imaging analysis
YEI El-Bouzaidi, O Abdoun - Scientific African, 2023 - Elsevier
In December 2019, the first case of coronavirus 2019 (COVID-19) appeared in China,
quickly leading to a global pandemic. Early and accurate diagnosis is crucial for effective …
quickly leading to a global pandemic. Early and accurate diagnosis is crucial for effective …
MTSS-AAE: Multi-task semi-supervised adversarial autoencoding for COVID-19 detection based on chest X-ray images
Efficient diagnosis of COVID-19 plays an important role in preventing the spread of the
disease. There are three major modalities to diagnose COVID-19 which include polymerase …
disease. There are three major modalities to diagnose COVID-19 which include polymerase …
Densely attention mechanism based network for COVID-19 detection in chest X-rays
Automatic COVID-19 detection using chest X-ray (CXR) can play a vital part in large-scale
screening and epidemic control. However, the radiographic features of CXR have different …
screening and epidemic control. However, the radiographic features of CXR have different …
Superficial white matter analysis: An efficient point-cloud-based deep learning framework with supervised contrastive learning for consistent tractography parcellation …
Diffusion MRI tractography is an advanced imaging technique that enables in vivo mapping
of the brain's white matter connections. White matter parcellation classifies tractography …
of the brain's white matter connections. White matter parcellation classifies tractography …
An adaptive deep metric learning loss function for class-imbalance learning via intraclass diversity and interclass distillation
Deep metric learning (DML) has been widely applied in various tasks (eg, medical diagnosis
and face recognition) due to the effective extraction of discriminant features via reducing …
and face recognition) due to the effective extraction of discriminant features via reducing …
Automatic identification of medically important mosquitoes using embedded learning approach-based image-retrieval system
V Kittichai, M Kaewthamasorn, Y Samung… - Scientific Reports, 2023 - nature.com
Mosquito-borne diseases such as dengue fever and malaria are the top 10 leading causes
of death in low-income countries. Control measure for the mosquito population plays an …
of death in low-income countries. Control measure for the mosquito population plays an …
[HTML][HTML] Federated Learning used for predicting outcomes in SARS-COV-2 patients
Abstract 'Federated Learning'(FL) is a method to train Artificial Intelligence (AI) models with
data from multiple sources while maintaining anonymity of the data thus removing many …
data from multiple sources while maintaining anonymity of the data thus removing many …
[HTML][HTML] Sketch-based semantic retrieval of medical images
The volume of medical images stored in hospitals is rapidly increasing; however, the
utilization of these accumulated medical images remains limited. Existing content-based …
utilization of these accumulated medical images remains limited. Existing content-based …