Automated detection and forecasting of covid-19 using deep learning techniques: A review
Abstract In March 2020, the World Health Organization (WHO) declared COVID-19 a global
epidemic, caused by the SARS-CoV-2 virus. Initially, COVID-19 was diagnosed using real …
epidemic, caused by the SARS-CoV-2 virus. Initially, COVID-19 was diagnosed using real …
A review of graph neural networks in epidemic modeling
Since the onset of the COVID-19 pandemic, there has been a growing interest in studying
epidemiological models. Traditional mechanistic models mathematically describe the …
epidemiological models. Traditional mechanistic models mathematically describe the …
[HTML][HTML] Technological advancements and elucidation gadgets for Healthcare applications: An exhaustive methodological review-part-I (AI, big data, block chain, open …
In the realm of the emergence and spread of infectious diseases with pandemic potential
throughout the history, plenty of pandemics (and epidemics), from the plague to AIDS (1981) …
throughout the history, plenty of pandemics (and epidemics), from the plague to AIDS (1981) …
[HTML][HTML] Artificial intelligence-driven prediction of COVID-19-related hospitalization and death: a systematic review
Aim To perform a systematic review on the use of Artificial Intelligence (AI) techniques for
predicting COVID-19 hospitalization and mortality using primary and secondary data …
predicting COVID-19 hospitalization and mortality using primary and secondary data …
[HTML][HTML] Deep learning in COVID-19 diagnosis, prognosis and treatment selection
S Jin, G Liu, Q Bai - Mathematics, 2023 - mdpi.com
Deep learning is a sub-discipline of artificial intelligence that uses artificial neural networks,
a machine learning technique, to extract patterns and make predictions from large datasets …
a machine learning technique, to extract patterns and make predictions from large datasets …
[HTML][HTML] A machine learning-based model for epidemic forecasting and faster drug discovery
KD Stergiou, GM Minopoulos, VA Memos… - Applied Sciences, 2022 - mdpi.com
Today, healthcare system models should have high accuracy and sensitivity so that patients
do not have a misdiagnosis. For this reason, sufficient knowledge of the area is required …
do not have a misdiagnosis. For this reason, sufficient knowledge of the area is required …
[HTML][HTML] DeepDynaForecast: Phylogenetic-informed graph deep learning for epidemic transmission dynamic prediction
In the midst of an outbreak or sustained epidemic, reliable prediction of transmission risks
and patterns of spread is critical to inform public health programs. Projections of …
and patterns of spread is critical to inform public health programs. Projections of …
[HTML][HTML] Unlocking insights: analysing COVID-19 lockdown policies and mobility data in Victoria, Australia, through a data-driven machine learning approach
The state of Victoria, Australia, implemented one of the world's most prolonged cumulative
lockdowns in 2020 and 2021. Although lockdowns have proven effective in managing …
lockdowns in 2020 and 2021. Although lockdowns have proven effective in managing …
CPSO: Chaotic Particle Swarm Optimization for Cluster Analysis
J Wang - Journal of Artificial Intelligence and Technology, 2023 - ojs.istp-press.com
Background: To solve the cluster analysis better, we propose a new method based on the
chaotic particle swarm optimization (CPSO) algorithm. Methods: In order to enhance the …
chaotic particle swarm optimization (CPSO) algorithm. Methods: In order to enhance the …
COVID‐19 vaccination strategies in Africa: A scoping review of the use of mathematical models to inform policy
Objective Mathematical models are vital tools to understand transmission dynamics and
assess the impact of interventions to mitigate COVID‐19. However, historically, their use in …
assess the impact of interventions to mitigate COVID‐19. However, historically, their use in …