Universal features of epidemic models under social distancing guidelines
Social distancing as a form of nonpharmaceutical intervention has been enacted in many
countries as a form of mitigating the spread of COVID-19. There has been a large interest in …
countries as a form of mitigating the spread of COVID-19. There has been a large interest in …
[HTML][HTML] Covid-19 imaging tools: How big data is big?
KC Santosh, S Ghosh - Journal of Medical Systems, 2021 - Springer
In this paper, considering year 2020 and Covid-19, we analyze medical imaging tools and
their performance scores in accordance with the dataset size and their complexity. For this …
their performance scores in accordance with the dataset size and their complexity. For this …
[HTML][HTML] Time to recovery from COVID-19 and its predictors among patients admitted to treatment center of Wollega University Referral Hospital (WURH), Western …
Introduction Despite its alarming spread throughout the world, no effective drug and vaccine
is discovered for COVID-19 so far. According to WHO, the recovery time from COVID-19 was …
is discovered for COVID-19 so far. According to WHO, the recovery time from COVID-19 was …
[HTML][HTML] Federated learning approach for early detection of chest lesion caused by COVID-19 infection using particle swarm optimization
DR Kandati, TR Gadekallu - Electronics, 2023 - mdpi.com
The chest lesion caused by COVID-19 infection pandemic is threatening the lives and well-
being of people all over the world. Artificial intelligence (AI)-based strategies are efficient …
being of people all over the world. Artificial intelligence (AI)-based strategies are efficient …
[HTML][HTML] SecureFed: federated learning empowered medical imaging technique to analyze lung abnormalities in chest X-rays
A Makkar, KC Santosh - International Journal of Machine Learning and …, 2023 - Springer
Abstract Machine learning is an effective and accurate technique to diagnose COVID-19
infections using image data, and chest X-Ray (CXR) is no exception. Considering privacy …
infections using image data, and chest X-Ray (CXR) is no exception. Considering privacy …
[HTML][HTML] Influenza-type epidemic risks by spatio-temporal Gaidai-Yakimov method
O Gaidai, V Yakimov, EJ van Loon - Dialogues in Health, 2023 - Elsevier
Background Global public health was recently hampered by reported widespread spread of
new coronavirus illness, although morbidity and fatality rates were low. Future coronavirus …
new coronavirus illness, although morbidity and fatality rates were low. Future coronavirus …
[HTML][HTML] Within host dynamics of SARS-CoV-2 in humans: Modeling immune responses and antiviral treatments
I Ghosh - SN Computer Science, 2021 - Springer
In December 2019, a newly discovered SARS-CoV-2 virus was emerged from China and
propagated worldwide as a pandemic, resulting in about 3–5% mortality. Mathematical …
propagated worldwide as a pandemic, resulting in about 3–5% mortality. Mathematical …
[HTML][HTML] Early administration of remdesivir to COVID-19 patients associates with higher recovery rate and lower need for ICU admission: A retrospective cohort study
HA Hussain Alsayed, F Saheb Sharif-Askari… - PloS one, 2021 - journals.plos.org
Objectives Remdesivir is one of the most widely recommended and used medications for
COVID-19 treatment. However, different outcomes have been reported for hospitalized …
COVID-19 treatment. However, different outcomes have been reported for hospitalized …
McS-Net: Multi-class Siamese network for severity of COVID-19 infection classification from lung CT scan slices
S Ahuja, BK Panigrahi, N Dey, A Taneja… - Applied Soft Computing, 2022 - Elsevier
Worldwide COVID-19 is a highly infectious and rapidly spreading disease in almost all age
groups. The Computed Tomography (CT) scans of lungs are found to be accurate for the …
groups. The Computed Tomography (CT) scans of lungs are found to be accurate for the …
Parameter identifiability and optimal control of an SARS-CoV-2 model early in the pandemic
We fit an SARS-CoV-2 model to US data of COVID-19 cases and deaths. We conclude that
the model is not structurally identifiable. We make the model identifiable by prefixing some of …
the model is not structurally identifiable. We make the model identifiable by prefixing some of …