Vision Transformers in medical computer vision—A contemplative retrospection

A Parvaiz, MA Khalid, R Zafar, H Ameer, M Ali… - … Applications of Artificial …, 2023 - Elsevier
Abstract Vision Transformers (ViTs), with the magnificent potential to unravel the information
contained within images, have evolved as one of the most contemporary and dominant …

[HTML][HTML] Utilisation of deep learning for COVID-19 diagnosis

S Aslani, J Jacob - Clinical Radiology, 2023 - Elsevier
The COVID-19 pandemic that began in 2019 has resulted in millions of deaths worldwide.
Over this period, the economic and healthcare consequences of COVID-19 infection in …

Development and evaluation of an artificial intelligence system for COVID-19 diagnosis

C **, W Chen, Y Cao, Z Xu, Z Tan, X Zhang… - Nature …, 2020 - nature.com
Early detection of COVID-19 based on chest CT enables timely treatment of patients and
helps control the spread of the disease. We proposed an artificial intelligence (AI) system for …

Blockchain-federated-learning and deep learning models for covid-19 detection using ct imaging

R Kumar, AA Khan, J Kumar, NA Golilarz… - IEEE Sensors …, 2021 - ieeexplore.ieee.org
With the increase of COVID-19 cases worldwide, an effective way is required to diagnose
COVID-19 patients. The primary problem in diagnosing COVID-19 patients is the shortage …

Covid-19 classification by FGCNet with deep feature fusion from graph convolutional network and convolutional neural network

SH Wang, VV Govindaraj, JM Górriz, X Zhang… - Information …, 2021 - Elsevier
Abstract (Aim) COVID-19 is an infectious disease spreading to the world this year. In this
study, we plan to develop an artificial intelligence based tool to diagnose on chest CT …

A deep learning approach to detect Covid-19 coronavirus with X-Ray images

G Jain, D Mittal, D Thakur, MK Mittal - Biocybernetics and biomedical …, 2020 - Elsevier
Rapid and accurate detection of COVID-19 coronavirus is necessity of time to prevent and
control of this pandemic by timely quarantine and medical treatment in absence of any …

A novel medical diagnosis model for COVID-19 infection detection based on deep features and Bayesian optimization

M Nour, Z Cömert, K Polat - Applied Soft Computing, 2020 - Elsevier
A pneumonia of unknown causes, which was detected in Wuhan, China, and spread rapidly
throughout the world, was declared as Coronavirus disease 2019 (COVID-19). Thousands …

Deep learning and medical image analysis for COVID-19 diagnosis and prediction

T Liu, E Siegel, D Shen - Annual review of biomedical …, 2022 - annualreviews.org
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 …

Federated semi-supervised learning for COVID region segmentation in chest CT using multi-national data from China, Italy, Japan

D Yang, Z Xu, W Li, A Myronenko, HR Roth… - Medical image …, 2021 - Elsevier
The recent outbreak of Coronavirus Disease 2019 (COVID-19) has led to urgent needs for
reliable diagnosis and management of SARS-CoV-2 infection. The current guideline is using …

Weakly supervised segmentation of COVID19 infection with scribble annotation on CT images

X Liu, Q Yuan, Y Gao, K He, S Wang, X Tang, J Tang… - Pattern recognition, 2022 - Elsevier
Segmentation of infections from CT scans is important for accurate diagnosis and follow-up
in tackling the COVID-19. Although the convolutional neural network has great potential to …