A5044473213- COVID-19 diagnosis using AI
- COVID-19 epidemiological studies
- Anomaly Detection Techniques and Applications
- Viral Infections and Outbreaks Research
- Data-Driven Disease Surveillance
- SARS-CoV-2 and COVID-19 Research
Kyungpook National University
2022-2024
The coronavirus disease (COVID-19) pandemic has spread rapidly across the world, creating an urgent need for predictive models that can help healthcare providers prepare and respond to outbreaks more quickly effectively, ultimately improve patient care. Early detection warning systems are crucial preventing controlling epidemic spread. In this study, we aimed propose a machine learning-based method predict transmission trend of COVID-19 new approach detect start time by analyzing...
<abstract> <p>COVID-19 is caused by the SARS-CoV-2 virus, which has produced variants and increasing concerns about a potential resurgence since pandemic outbreak in 2019. Predicting infectious disease outbreaks crucial for effective prevention control. This study aims to predict transmission patterns of COVID-19 using machine learning, such as support vector machine, random forest, XGBoost, confirmed cases, death imported respectively. The categorizes trends into three groups:...
<sec> <title>BACKGROUND</title> In the face of rapid spread coronavirus disease (COVID-19) pandemic, predicting COVID-19 can help healthcare providers prepare and respond to outbreaks more quickly effectively, ultimately leading better care for patients. </sec> <title>OBJECTIVE</title> We aimed develop a method detect early or identify potential using machine learning (ML) by analyzing epidemiological data in Republic Korea. <title>METHODS</title> ML methods were developed predict...