[HTML][HTML] Multilayer and multiplex networks: An introduction to their use in veterinary epidemiology

AC Kinsley, G Rossi, MJ Silk… - Frontiers in veterinary …, 2020 - frontiersin.org
Contact network analysis has become a vital tool for conceptualizing the spread of
pathogens in animal populations and is particularly useful for understanding the implications …

[HTML][HTML] Machine learning-based farm risk management: A systematic mapping review

S Ghaffarian, M van der Voort, J Valente… - … and electronics in …, 2022 - Elsevier
Farms face various risks such as uncertainties in the natural growth process, obtaining
adequate financing, volatile input and output prices, unpredictable changes in farm-related …

[HTML][HTML] Neural network based country wise risk prediction of COVID-19

R Pal, AA Sekh, S Kar, DK Prasad - Applied Sciences, 2020 - mdpi.com
The recent worldwide outbreak of the novel coronavirus (COVID-19) has opened up new
challenges to the research community. Artificial intelligence (AI) driven methods can be …

Prediction for global African swine fever outbreaks based on a combination of random forest algorithms and meteorological data

R Liang, Y Lu, X Qu, Q Su, C Li, S Xia… - Transboundary and …, 2020 - Wiley Online Library
African swine fever (ASF) is a virulent infectious disease of pigs. As there is no effective
vaccine and treatment method at present, it poses a great threat to the pig industry once it …

Machine learning-based prediction of phases in high-entropy alloys

R Machaka - Computational Materials Science, 2021 - Elsevier
Abstract “The answer to the question “why HEAs exhibit such exceptional properties” lies in
their phases”[1]. The implementation of machine learning (ML) approaches for the …

[HTML][HTML] Implementation of stacking based ARIMA model for prediction of Covid-19 cases in India

A Swaraj, K Verma, A Kaur, G Singh, A Kumar… - Journal of biomedical …, 2021 - Elsevier
Background Time-series forecasting has a critical role during pandemics as it provides
essential information that can lead to abstaining from the spread of the disease. The novel …

Modelling and Simulation of COVID-19 Outbreak Prediction Using Supervised Machine Learning.

R Zagrouba, MA Khan, MA Saleem… - Computers …, 2021 - search.ebscohost.com
Abstract Novel Coronavirus-19 (COVID-19) is a newer type of coronavirus that has not been
formally detected in humans. It is established that this disease often affects people of …

[HTML][HTML] Assessment of the outbreak risk, mapping and infection behavior of COVID-19: Application of the autoregressive integrated-moving average (ARIMA) and …

HR Pourghasemi, S Pouyan, Z Farajzadeh… - Plos one, 2020 - journals.plos.org
Infectious disease outbreaks pose a significant threat to human health worldwide. The
outbreak of pandemic coronavirus disease 2019 (COVID-19) has caused a global health …

Hi-COVIDNet: Deep learning approach to predict inbound COVID-19 patients and case study in South Korea

M Kim, J Kang, D Kim, H Song, H Min, Y Nam… - Proceedings of the 26th …, 2020 - dl.acm.org
The escalating crisis of COVID-19 has put people all over the world in danger. Owing to the
high contagion rate of the virus, COVID-19 cases continue to increase globally. To further …

[HTML][HTML] A random forest model for peptide classification based on virtual docking data

H Feng, F Wang, N Li, Q Xu, G Zheng, X Sun… - International Journal of …, 2023 - mdpi.com
The affinity of peptides is a crucial factor in studying peptide–protein interactions. Despite
the development of various techniques to evaluate peptide–receptor affinity, the results may …