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Statistical modeling for the prediction of infectious disease dissemination with special reference to COVID-19 spread
In this review, we have discussed the different statistical modeling and prediction techniques
for various infectious diseases including the recent pandemic of COVID-19. The distribution …
for various infectious diseases including the recent pandemic of COVID-19. The distribution …
COVID-19 impact on global maritime mobility
To prevent the outbreak of the Coronavirus disease (COVID-19), many countries around the
world went into lockdown and imposed unprecedented containment measures. These …
world went into lockdown and imposed unprecedented containment measures. These …
Analysis and prediction of COVID-19 using SIR, SEIQR, and machine learning models: Australia, Italy, and UK cases
The novel coronavirus disease, also known as COVID-19, is a disease outbreak that was
first identified in Wuhan, a Central Chinese city. In this report, a short analysis focusing on …
first identified in Wuhan, a Central Chinese city. In this report, a short analysis focusing on …
Optimized pollard route deviation and route selection using Bayesian machine learning techniques in wireless sensor networks
Optimal route selection and circumventing the route deviation is essential in sensor
transmission to reach the destination properly and to save energy in sensors. Wireless …
transmission to reach the destination properly and to save energy in sensors. Wireless …
Uncovering hidden and complex relations of pandemic dynamics using an AI driven system
The COVID-19 pandemic continues to challenge healthcare systems globally, necessitating
advanced tools for clinical decision support. Amidst the complexity of COVID-19 …
advanced tools for clinical decision support. Amidst the complexity of COVID-19 …
Are CDS spreads predictable during the Covid-19 pandemic? Forecasting based on SVM, GMDH, LSTM and Markov switching autoregression
This paper investigates the forecasting performance for credit default swap (CDS) spreads
by Support Vector Machines (SVM), Group Method of Data Handling (GMDH), Long Short …
by Support Vector Machines (SVM), Group Method of Data Handling (GMDH), Long Short …
A review on Indian state/City Covid-19 cases outbreak forecast utilizing machine learning models
Several scene supposition models for COVID-19 are being utilized by experts around the
globe to settle on trained choices and keep up fitting control measures. Man-made …
globe to settle on trained choices and keep up fitting control measures. Man-made …
[HTML][HTML] Medical Resource Management in Emergency Hierarchical Diagnosis and Treatment Systems: A Research Framework
L Luo, R Zhang, M Zhuo, R Shan, Z Yu, W Li, P Wu… - Healthcare, 2024 - mdpi.com
The occurrence of major public health crises, like the COVID-19 epidemic, present
significant challenges to healthcare systems and the management of emergency medical …
significant challenges to healthcare systems and the management of emergency medical …
A dynamic approach to support outbreak management using reinforcement learning and semi-connected SEIQR models
Y Kao, PJ Chu, PC Chou, CC Chen - BMC Public Health, 2024 - Springer
Background Containment measures slowed the spread of COVID-19 but led to a global
economic crisis. We establish a reinforcement learning (RL) algorithm that balances disease …
economic crisis. We establish a reinforcement learning (RL) algorithm that balances disease …
Quickest detection of COVID-19 pandemic onset
This letter develops an easily-implementable version of Page's CUSUM quickest-detection
test, designed to work in certain composite hypothesis scenarios with time-varying data …
test, designed to work in certain composite hypothesis scenarios with time-varying data …