COVID-19 image classification using deep learning: Advances, challenges and opportunities

P Aggarwal, NK Mishra, B Fatimah, P Singh… - Computers in Biology …, 2022 - Elsevier
Abstract Corona Virus Disease-2019 (COVID-19), caused by Severe Acute Respiratory
Syndrome-Corona Virus-2 (SARS-CoV-2), is a highly contagious disease that has affected …

Automated detection and forecasting of covid-19 using deep learning techniques: A review

A Shoeibi, M Khodatars, M Jafari, N Ghassemi… - Neurocomputing, 2024 - Elsevier
Abstract In March 2020, the World Health Organization (WHO) declared COVID-19 a global
epidemic, caused by the SARS-CoV-2 virus. Initially, COVID-19 was diagnosed using real …

Application of deep learning techniques in diagnosis of covid-19 (coronavirus): a systematic review

YH Bhosale, KS Patnaik - Neural processing letters, 2023 - Springer
Covid-19 is now one of the most incredibly intense and severe illnesses of the twentieth
century. Covid-19 has already endangered the lives of millions of people worldwide due to …

Lung segmentation and automatic detection of COVID-19 using radiomic features from chest CT images

C Zhao, Y Xu, Z He, J Tang, Y Zhang, J Han, Y Shi… - Pattern Recognition, 2021 - Elsevier
This paper aims to develop an automatic method to segment pulmonary parenchyma in
chest CT images and analyze texture features from the segmented pulmonary parenchyma …

Covid-net ct-2: Enhanced deep neural networks for detection of covid-19 from chest ct images through bigger, more diverse learning

H Gunraj, A Sabri, D Koff, A Wong - Frontiers in Medicine, 2022 - frontiersin.org
The COVID-19 pandemic continues to rage on, with multiple waves causing substantial
harm to health and economies around the world. Motivated by the use of computed …

CO-IRv2: Optimized InceptionResNetV2 for COVID-19 detection from chest CT images

MRH Mondal, S Bharati, P Podder - PloS one, 2021 - journals.plos.org
This paper focuses on the application of deep learning (DL) in the diagnosis of coronavirus
disease (COVID-19). The novelty of this work is in the introduction of optimized …

Deep learning model for the automatic classification of COVID-19 pneumonia, non-COVID-19 pneumonia, and the healthy: a multi-center retrospective study

M Nishio, D Kobayashi, E Nishioka, H Matsuo… - Scientific Reports, 2022 - nature.com
This retrospective study aimed to develop and validate a deep learning model for the
classification of coronavirus disease-2019 (COVID-19) pneumonia, non-COVID-19 …

COVID-19-the role of artificial intelligence, machine learning, and deep learning: a newfangled

DN Vinod, SRS Prabaharan - Archives of Computational Methods in …, 2023 - Springer
The absolute previously infected novel coronavirus (COVID-19) was found in Wuhan, China,
in December 2019. The COVID-19 epidemic has spread to more than 220 nations and …

Helping hearing-impaired in emergency situations: A deep learning-based approach

QM Areeb, M Nadeem, R Alroobaea, F Anwer - IEEE Access, 2022 - ieeexplore.ieee.org
Hearing-impaired people use sign language to express their thoughts and emotions and
reinforce information delivered in daily conversations. Though they make a significant …

Optimization in the context of COVID-19 prediction and control: A literature review

E Jordan, DE Shin, S Leekha, S Azarm - Ieee Access, 2021 - ieeexplore.ieee.org
This paper presents an overview of some key results from a body of optimization studies that
are specifically related to COVID-19, as reported in the literature during 2020-2021. As …