Taewan Goo
Biographic Data
| ID | 7863673 |
|---|---|
| NAME | Taewan Goo |
| GIVEN NAMES | Taewan |
| FAMILY NAME | Goo |
| SIGNATURE | GOO T |
| AFFILIATIONS | Seoul National University |
| ORCID | 0000-0001-9427-2290 |
| VERIFIED | Yes |
| TOTAL WORKS | 4 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 4 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2021 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
An ensemble approach improves the prediction of the Covid-19 pandemic in South Korea
Background: Modelling can contribute to disease prevention and control strategies. Accurate predictions of future cases and mortality rates were essential for establishing appropriate policies during the COVID-19 pandemic. However, no single model yielded definite conclusions, with each having specific strengths and weaknesses. Here we propose an ensemble learning approach which can offset the limitations of each model and improve prediction perf…
K-Track-Covid: Interactive web-based dashboard for analyzing geographical and temporal spread of Covid-19 in South Korea
The COVID-19 pandemic has necessitated the development of robust tools for tracking and modeling the spread of the virus. We present ‘K-Track-Covid,’ an interactive web-based dashboard developed using the R Shiny framework, to offer users an intuitive dashboard for analyzing the geographical and temporal spread of COVID-19 in South Korea. Our dashboard employs dynamic user interface elements, employs validated epidemiological models, and integrat…
Statistical Estimation of Effects of Implemented Government Policies on Covid-19 Situation in South Korea
Since the outbreak of novel SARS-COV-2, each country has implemented diverse policies to mitigate and suppress the spread of the virus. However, no systematic evaluation of these policies in their alleviation of the pandemic has been done. We investigate the impact of five indices derived from 12 policies in the Oxford COVID-19 Government Response Tracker dataset and the Korean government's index, which is the social distancing level implemented …
Which National Factors Are Most Influential in the Spread of Covid-19
The outbreak of the novel COVID-19, declared a global pandemic by WHO, is the most serious public health threat seen in terms of respiratory viruses since the 1918 H1N1 influenza pandemic. It is surprising that the total number of COVID-19 confirmed cases and the number of deaths has varied greatly across countries. Such great variations are caused by age population, health conditions, travel, economy, and environmental factors. Here, we investig…
No prominent works on this page.
Statistical Estimation of Effects of Implemented Government Policies on Covid-19 Situation in South Korea
Since the outbreak of novel SARS-COV-2, each country has implemented diverse policies to mitigate and suppress the spread of the virus. However, no systematic evaluation of these policies in their alleviation of the pandemic has been done. We investigate the impact of five indices derived from 12 policies in the Oxford COVID-19 Government Response Tracker dataset and the Korean government's index, which is the social distancing level implemented …
Which National Factors Are Most Influential in the Spread of Covid-19
The outbreak of the novel COVID-19, declared a global pandemic by WHO, is the most serious public health threat seen in terms of respiratory viruses since the 1918 H1N1 influenza pandemic. It is surprising that the total number of COVID-19 confirmed cases and the number of deaths has varied greatly across countries. Such great variations are caused by age population, health conditions, travel, economy, and environmental factors. Here, we investig…
K-Track-Covid: Interactive web-based dashboard for analyzing geographical and temporal spread of Covid-19 in South Korea
The COVID-19 pandemic has necessitated the development of robust tools for tracking and modeling the spread of the virus. We present ‘K-Track-Covid,’ an interactive web-based dashboard developed using the R Shiny framework, to offer users an intuitive dashboard for analyzing the geographical and temporal spread of COVID-19 in South Korea. Our dashboard employs dynamic user interface elements, employs validated epidemiological models, and integrat…
An ensemble approach improves the prediction of the Covid-19 pandemic in South Korea
Background: Modelling can contribute to disease prevention and control strategies. Accurate predictions of future cases and mortality rates were essential for establishing appropriate policies during the COVID-19 pandemic. However, no single model yielded definite conclusions, with each having specific strengths and weaknesses. Here we propose an ensemble learning approach which can offset the limitations of each model and improve prediction perf…
COVID-19 epidemiological studies (4 works) · Medicine (4 works) · Outbreak (4 works) · Pandemic (4 works) · Virology (4 works) · Geography (3 works) · 2019-20 coronavirus outbreak (2 works) · Computer Science (2 works) · Coronavirus disease 2019 (COVID-19 (2 works) · COVID-19 Pandemic Impacts (2 works)