A novel deep fusion strategy for COVID-19 prediction using multimodality approach
Over the last two years, the novel coronavirus has become a significant threat to the health
of the public, and numerous approaches are developed to determine the symptoms of …
of the public, and numerous approaches are developed to determine the symptoms of …
COVID-RDNet: A novel coronavirus pneumonia classification model using the mixed dataset by CT and X-rays images
L Fang, X Wang - biocybernetics and biomedical engineering, 2022 - Elsevier
Abstract Corona virus disease 2019 (COVID-19) testing relies on traditional screening
methods, which require a lot of manpower and material resources. Recently, to effectively …
methods, which require a lot of manpower and material resources. Recently, to effectively …
MFA-Net: Multiple Feature Association Network for medical image segmentation
Z Li, N Zhang, H Gong, R Qiu, W Zhang - Computers in Biology and …, 2023 - Elsevier
Medical image segmentation plays a crucial role in computer-aided diagnosis. However,
due to the large variability of medical images, accurate segmentation is a highly challenging …
due to the large variability of medical images, accurate segmentation is a highly challenging …
Towards Automated Multiclass Severity Prediction Approach for COVID‐19 Infections Based on Combinations of Clinical Data
The recent dramatic expansion of the COVID‐19 outbreak is placing enormous strain on
human society as a whole. Numerous biomarkers are being investigated in an effort to track …
human society as a whole. Numerous biomarkers are being investigated in an effort to track …
A survey of progress on cooperative multi-agent reinforcement learning in open environment
Multi-agent Reinforcement Learning (MARL) has gained wide attention in recent years and
has made progress in various fields. Specifically, cooperative MARL focuses on training a …
has made progress in various fields. Specifically, cooperative MARL focuses on training a …
Edge intelligence-assisted smart healthcare solution for health pandemic: a federated environment approach
Deep Learning (DL) has emerged as the most effective approach for COVID-19 detection,
but privacy concerns hinder its performance due to limited data sharing by medical …
but privacy concerns hinder its performance due to limited data sharing by medical …
Weakly supervised segmentation of COVID-19 infection with local lesion coherence on CT images
W Sun, X Feng, J Liu, H Ma - Biomedical signal processing and control, 2023 - Elsevier
At the end of 2019, a novel coronavirus, COVID-19, was ravaging the world, wreaking havoc
on public health and the global economy. Today, although Reverse Transcription …
on public health and the global economy. Today, although Reverse Transcription …
Diagnosis of COVID‐19 Disease in Chest CT‐Scan Images Based on Combination of Low‐Level Texture Analysis and MobileNetV2 Features
A Yazdani, S Fekri-Ershad… - Computational …, 2022 - Wiley Online Library
Since two years ago, the COVID‐19 virus has spread strongly in the world and has killed
more than 6 million people directly and has affected the lives of more than 500 million …
more than 6 million people directly and has affected the lives of more than 500 million …
Detection of COVID-19 from deep breathing sounds using sound spectrum with image augmentation and deep learning techniques
The COVID-19 pandemic is one of the most disruptive outbreaks of the 21st century
considering its impacts on our freedoms and social lifestyle. Several methods have been …
considering its impacts on our freedoms and social lifestyle. Several methods have been …
COVID-19 detection from chest X-ray images based on deep learning techniques
The COVID-19 pandemic has posed significant challenges in accurately diagnosing the
disease, as severe cases may present symptoms similar to pneumonia. Real-Time Reverse …
disease, as severe cases may present symptoms similar to pneumonia. Real-Time Reverse …