[HTML][HTML] Adoption of digital technologies in health care during the COVID-19 pandemic: systematic review of early scientific literature

D Golinelli, E Boetto, G Carullo, AG Nuzzolese… - Journal of medical …, 2020 - jmir.org
Background The COVID-19 pandemic is favoring digital transitions in many industries and in
society as a whole. Health care organizations have responded to the first phase of the …

Review of artificial intelligence techniques in imaging data acquisition, segmentation, and diagnosis for COVID-19

F Shi, J Wang, J Shi, Z Wu, Q Wang… - IEEE reviews in …, 2020 - ieeexplore.ieee.org
The pandemic of coronavirus disease 2019 (COVID-19) is spreading all over the world.
Medical imaging such as X-ray and computed tomography (CT) plays an essential role in …

Exploring the effect of image enhancement techniques on COVID-19 detection using chest X-ray images

T Rahman, A Khandakar, Y Qiblawey, A Tahir… - Computers in biology …, 2021 - Elsevier
Computer-aided diagnosis for the reliable and fast detection of coronavirus disease (COVID-
19) has become a necessity to prevent the spread of the virus during the pandemic to ease …

CoroDet: A deep learning based classification for COVID-19 detection using chest X-ray images

E Hussain, M Hasan, MA Rahman, I Lee… - Chaos, Solitons & …, 2021 - Elsevier
Abstract Background and Objective The Coronavirus 2019, or shortly COVID-19, is a viral
disease that causes serious pneumonia and impacts our different body parts from mild to …

Classification of the COVID-19 infected patients using DenseNet201 based deep transfer learning

A Jaiswal, N Gianchandani, D Singh… - Journal of …, 2021 - Taylor & Francis
Deep learning models are widely used in the automatic analysis of radiological images.
These techniques can train the weights of networks on large datasets as well as fine tuning …

Automated detection of COVID-19 cases using deep neural networks with X-ray images

T Ozturk, M Talo, EA Yildirim, UB Baloglu… - Computers in biology …, 2020 - Elsevier
Abstract The novel coronavirus 2019 (COVID-2019), which first appeared in Wuhan city of
China in December 2019, spread rapidly around the world and became a pandemic. It has …

[HTML][HTML] Deep-chest: Multi-classification deep learning model for diagnosing COVID-19, pneumonia, and lung cancer chest diseases

DM Ibrahim, NM Elshennawy, AM Sarhan - Computers in biology and …, 2021 - Elsevier
Abstract Corona Virus Disease (COVID-19) has been announced as a pandemic and is
spreading rapidly throughout the world. Early detection of COVID-19 may protect many …

Inf-net: Automatic covid-19 lung infection segmentation from ct images

DP Fan, T Zhou, GP Ji, Y Zhou, G Chen… - IEEE transactions on …, 2020 - ieeexplore.ieee.org
Coronavirus Disease 2019 (COVID-19) spread globally in early 2020, causing the world to
face an existential health crisis. Automated detection of lung infections from computed …

COVID-19 detection through transfer learning using multimodal imaging data

MJ Horry, S Chakraborty, M Paul, A Ulhaq… - Ieee …, 2020 - ieeexplore.ieee.org
Detecting COVID-19 early may help in devising an appropriate treatment plan and disease
containment decisions. In this study, we demonstrate how transfer learning from deep …

Covid-ct-dataset: a ct scan dataset about covid-19

X Yang, X He, J Zhao, Y Zhang, S Zhang… - arXiv preprint arXiv …, 2020 - arxiv.org
During the outbreak time of COVID-19, computed tomography (CT) is a useful manner for
diagnosing COVID-19 patients. Due to privacy issues, publicly available COVID-19 CT …