Applications of machine learning and artificial intelligence for Covid-19 (SARS-CoV-2) pandemic: A review

S Lalmuanawma, J Hussain, L Chhakchhuak - Chaos, Solitons & Fractals, 2020 - Elsevier
Background and objective During the recent global urgency, scientists, clinicians, and
healthcare experts around the globe keep on searching for a new technology to support in …

COVID-19 in the age of artificial intelligence: a comprehensive review

J Rasheed, A Jamil, AA Hameed, F Al-Turjman… - Interdisciplinary …, 2021 - Springer
The recent COVID-19 pandemic, which broke at the end of the year 2019 in Wuhan, China,
has infected more than 98.52 million people by today (January 23, 2021) with over 2.11 …

[HTML][HTML] Comparative study of machine learning methods for COVID-19 transmission forecasting

A Dairi, F Harrou, A Zeroual, MM Hittawe… - Journal of biomedical …, 2021 - Elsevier
Within the recent pandemic, scientists and clinicians are engaged in seeking new
technology to stop or slow down the COVID-19 pandemic. The benefit of machine learning …

Ladybug Beetle Optimization algorithm: application for real-world problems

S Safiri, A Nikoofard - The Journal of Supercomputing, 2023 - Springer
In this paper, a novel optimization algorithm is proposed, called the Ladybug Beetle
Optimization (LBO) algorithm, which is inspired by the behavior of ladybugs in nature when …

Determining causal relationships in leadership research using Machine Learning: The powerful synergy of experiments and data science

A Lee, I Inceoglu, O Hauser, M Greene - The Leadership Quarterly, 2022 - Elsevier
Abstract Machine Learning (ML) techniques offer exciting new avenues for leadership
research. In this paper we discuss how ML techniques can be used to inform predictive and …

Leveraging brain modularity prior for interpretable representation learning of fMRI

Q Wang, W Wang, Y Fang, PT Yap… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
Resting-state functional magnetic resonance imaging (rs-fMRI) can reflect spontaneous
neural activities in the brain and is widely used for brain disorder analysis. Previous studies …

Classification of schizophrenia from functional MRI using large-scale extended Granger causality

A Wismüller, MA Vosoughi - Medical Imaging 2021: Computer …, 2021 - spiedigitallibrary.org
The literature manifests that schizophrenia is associated with alterations in brain network
connectivity. We investigate whether large-scale Extended Granger Causality (lsXGC) can …

Large-scale kernelized granger causality (lskgc) for inferring topology of directed graphs in brain networks

MA Vosoughi, A Wismüller - Medical Imaging 2022 …, 2022 - spiedigitallibrary.org
Graph topology inference in networks with co-evolving and interacting time-series is crucial
for network studies. Vector autoregressive models (VAR) are popular approaches for …

Deep learning-based drug screening for covid-19 and case studies

KM Saravanan, H Zhang, MT Hossain, MS Reza… - In Silico Modeling of …, 2021 - Springer
Abstract Coronavirus infectious disease (COVID-19), caused by deadly severe acute
respiratory syndrome coronavirus 2 (SARS-CoV-2), has been declared as a pandemic by …

Large-scale extended granger causality for classification of marijuana users from functional mri

MA Vosoughi, A Wismüller - Medical Imaging 2021 …, 2021 - spiedigitallibrary.org
It has been shown in the literature that marijuana use is associated with changes in brain
network connectivity. We investigate whether large-scale Extended Granger Causality …