COVID-19 modeling: A review

L Cao, Q Liu - ACM Computing Surveys, 2024 - dl.acm.org
The SARS-CoV-2 viruses and their triggered COVID-19 pandemic have fundamentally
reshaped the world in almost every aspect, their evolution and influences remain. While over …

Graph Artificial Intelligence in Medicine

R Johnson, MM Li, A Noori, O Queen… - Annual Review of …, 2024 - annualreviews.org
In clinical artificial intelligence (AI), graph representation learning, mainly through graph
neural networks and graph transformer architectures, stands out for its capability to capture …

Leveraging deep-learning and unconventional data for real-time surveillance, forecasting, and early warning of respiratory pathogens outbreak

ZM Nia, L Seyyed-Kalantari, M Goitom… - Artificial Intelligence in …, 2025 - Elsevier
Background Controlling re-emerging outbreaks such as COVID-19 is a critical concern to
global health. Disease forecasting solutions are extremely beneficial to public health …

Advances in the development of representation learning and its innovations against COVID-19

P Li, MM Parvej, C Zhang, S Guo, J Zhang - COVID, 2023 - mdpi.com
In bioinformatics research, traditional machine-learning methods have demonstrated
efficacy in addressing Euclidean data. However, real-world data often encompass non …

Role of Fluid Dynamics in Infectious Disease Transmission: Insights from COVID-19 and Other Pathogens

S Koley - Trends in Sciences, 2024 - tis.wu.ac.th
The spread of infectious diseases such as COVID-19 depends on complex fluid dynamics
interactions between pathogens and fluid phases, including individual droplets and …

Mathematical analysis on novel coronavirus model using HPM

S Anitha, KVT Selvi… - E3S Web of Conferences, 2024 - e3s-conferences.org
An analysis of the model underpinning the description of the spread of coronavirus infection
reservoir (seafood market) is examined in detail in this work. We considered the infection …