[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 …

Applications of artificial intelligence in COVID-19 pandemic: A comprehensive review

M Khan, MT Mehran, ZU Haq, Z Ullah, SR Naqvi… - Expert systems with …, 2021 - Elsevier
During the current global public health emergency caused by novel coronavirus disease 19
(COVID-19), researchers and medical experts started working day and night to search for …

A review of mathematical modeling, artificial intelligence and datasets used in the study, prediction and management of COVID-19

Y Mohamadou, A Halidou, PT Kapen - Applied Intelligence, 2020 - Springer
In the past few months, several works were published in regards to the dynamics and early
detection of COVID-19 via mathematical modeling and Artificial intelligence (AI). The aim of …

Review on COVID‐19 diagnosis models based on machine learning and deep learning approaches

ZAA Alyasseri, MA Al‐Betar, IA Doush… - Expert …, 2022 - Wiley Online Library
COVID‐19 is the disease evoked by a new breed of coronavirus called the severe acute
respiratory syndrome coronavirus 2 (SARS‐CoV‐2). Recently, COVID‐19 has become a …

Deep learning-based meta-classifier approach for COVID-19 classification using CT scan and chest X-ray images

V Ravi, H Narasimhan, C Chakraborty, TD Pham - Multimedia systems, 2022 - Springer
Literature survey shows that convolutional neural network (CNN)-based pretrained models
have been largely used for CoronaVirus Disease 2019 (COVID-19) classification using …

Role of intelligent computing in COVID-19 prognosis: A state-of-the-art review

H Swapnarekha, HS Behera, J Nayak, B Naik - Chaos, Solitons & Fractals, 2020 - Elsevier
Abstract The World Health Organization (WHO) declared novel coronavirus 2019 (COVID-
19), an infectious epidemic caused by SARS-CoV-2, as Pandemic in March 2020. It has …

Mitigating bias in radiology machine learning: 2. Model development

K Zhang, B Khosravi, S Vahdati, S Faghani… - Radiology: Artificial …, 2022 - pubs.rsna.org
There are increasing concerns about the bias and fairness of artificial intelligence (AI)
models as they are put into clinical practice. Among the steps for implementing machine …

A multichannel EfficientNet deep learning-based stacking ensemble approach for lung disease detection using chest X-ray images

V Ravi, V Acharya, M Alazab - Cluster Computing, 2023 - Springer
This paper proposes a multichannel deep learning approach for lung disease detection
using chest X-rays. The multichannel models used in this work are EfficientNetB0 …

Biphasic majority voting-based comparative COVID-19 diagnosis using chest X-ray images

KM Sunnetci, A Alkan - Expert Systems with Applications, 2023 - Elsevier
The COVID-19 pandemic has been affecting the world since December 2019, and
nowadays, the number of infected is increasing rapidly. Chest X-ray images are clinical …

Automatic prediction of COVID− 19 from chest images using modified ResNet50

M Elpeltagy, H Sallam - Multimedia tools and applications, 2021 - Springer
Abstract Recently coronavirus 2019 (COVID-2019), discovered in Wuhan city of China in
December 2019 announced as world pandemic by the World Health Organization (WHO). It …