Deep learning: Applications, architectures, models, tools, and frameworks: A comprehensive survey
M Gheisari, F Ebrahimzadeh, M Rahimi… - CAAI Transactions …, 2023 - Wiley Online Library
Deep Learning (DL) is a subfield of machine learning that significantly impacts extracting
new knowledge. By using DL, the extraction of advanced data representations and …
new knowledge. By using DL, the extraction of advanced data representations and …
Machine learning in detection and classification of leukemia using smear blood images: a systematic review
Introduction. The early detection and diagnosis of leukemia, ie, the precise differentiation of
malignant leukocytes with minimum costs in the early stages of the disease, is a major …
malignant leukocytes with minimum costs in the early stages of the disease, is a major …
Automated detection of COVID-19 cases from chest X-ray images using deep neural network and XGBoost
Introduction In late 2019 and after the COVID-19 pandemic in the world, many researchers
and scholars tried to provide methods for detecting COVID-19 cases. Accordingly, this study …
and scholars tried to provide methods for detecting COVID-19 cases. Accordingly, this study …
A privacy-aware method for COVID-19 detection in chest CT images using lightweight deep conventional neural network and blockchain
A Heidari, S Toumaj, NJ Navimipour, M Unal - Computers in Biology and …, 2022 - Elsevier
With the global spread of the COVID-19 epidemic, a reliable method is required for
identifying COVID-19 victims. The biggest issue in detecting the virus is a lack of testing kits …
identifying COVID-19 victims. The biggest issue in detecting the virus is a lack of testing kits …
[HTML][HTML] Deep convolutional neural network–based computer-aided detection system for COVID-19 using multiple lung scans: design and implementation study
Background Owing to the COVID-19 pandemic and the imminent collapse of health care
systems following the exhaustion of financial, hospital, and medicinal resources, the World …
systems following the exhaustion of financial, hospital, and medicinal resources, the World …
[HTML][HTML] Application of deep learning and machine learning models to improve healthcare in sub-Saharan Africa: Emerging opportunities, trends and implications
E Mbunge, J Batani - Telematics and Informatics Reports, 2023 - Elsevier
Deep learning and machine learning techniques present unmatched opportunities to
improve healthcare in sub-Saharan Africa (SSA). However, there is a paucity of literature on …
improve healthcare in sub-Saharan Africa (SSA). However, there is a paucity of literature on …
A Survey of Deep Learning Techniques for the Analysis of COVID-19 and their usability for Detecting Omicron
ABSTRACT The Coronavirus (COVID-19) outbreak in December 2019 has drastically
affected humans worldwide, creating a health crisis that has infected millions of lives and …
affected humans worldwide, creating a health crisis that has infected millions of lives and …
Role of artificial intelligence in COVID-19 detection
The global pandemic of coronavirus disease (COVID-19) has caused millions of deaths and
affected the livelihood of many more people. Early and rapid detection of COVID-19 is a …
affected the livelihood of many more people. Early and rapid detection of COVID-19 is a …
Supervised and weakly supervised deep learning models for COVID-19 CT diagnosis: A systematic review
Artificial intelligence (AI) and computer vision (CV) methods become reliable to extract
features from radiological images, aiding COVID-19 diagnosis ahead of the pathogenic tests …
features from radiological images, aiding COVID-19 diagnosis ahead of the pathogenic tests …
Artificial intelligence in surveillance, diagnosis, drug discovery and vaccine development against COVID-19
As of August 6th, 2021, the World Health Organization has notified 200.8 million laboratory-
confirmed infections and 4.26 million deaths from COVID-19, making it the worst pandemic …
confirmed infections and 4.26 million deaths from COVID-19, making it the worst pandemic …