Taesung Park
Biographic Data
| ID | 4004480 |
|---|---|
| NAME | Taesung Park |
| GIVEN NAMES | Taesung |
| FAMILY NAME | Park |
| SIGNATURE | PARK T |
| AFFILIATIONS | Seoul National University |
| ORCID | 0000-0002-8294-590X |
| VERIFIED | Yes |
| TOTAL WORKS | 11 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 11 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2012 |
| 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…
Machine learning models to predict the maximum severity of Covid-19 based on initial hospitalization record
Background: As the worldwide spread of coronavirus disease 2019 (COVID-19) continues for a long time, early prediction of the maximum severity is required for effective treatment of each patient. Objective: This study aimed to develop predictive models for the maximum severity of hospitalized COVID-19 patients using artificial intelligence (AI)/machine learning (ML) algorithms. Methods: The medical records of 2,263 COVID-19 patients admitted to 1…
A statistical look at the Covid-19 vaccine development and vaccine policies
The global outbreak of COVID-19 caused by the SARS-CoV-2 virus elicited immense global interest in the development and distribution of safe COVID-19 vaccines by various governments and researchers, capable of stopping the spread of COVID-19 disease. After COVID-19 was declared a global pandemic, several vaccines have been developed for emergency use authorization. The accelerated development of the vaccines was attributed to many factors but main…
Statistical modeling of health space based on metabolic stress and oxidative stress scores
These validation studies using two independent datasets successfully demonstrated the usefulness of the proposed HS
A Deep Learning Algorithm to Predict Hazardous Drinkers and the Severity of Alcohol-Related Problems Using K-NHANES
Purpose: The number of patients with alcohol-related problems is steadily increasing. A large-scale survey of alcohol-related problems has been conducted. However, studies that predict hazardous drinkers and identify which factors contribute to the prediction are limited. Thus, the purpose of this study was to predict hazardous drinkers and the severity of alcohol-related problems of patients using a deep learning algorithm based on a large-scale…
Estimation of Undetected Asymptomatic Covid-19 Cases in South Korea Using a Probabilistic Model
Increasing evidence shows that many infections of COVID-19 are asymptomatic, becoming a global challenge, since asymptomatic infections have the same infectivity as symptomatic infections. We developed a probabilistic model for estimating the proportion of undetected asymptomatic COVID-19 patients in the country. We considered two scenarios: one is conservative and the other is nonconservative. By combining the above two scenarios, we gave an int…
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…
Do we need to reconsider the CMAM admission and discharge criteria?; an analysis of CMAM data in South Sudan
The relative velocity of MUAC 3 gain was suggested as a proxy measure for volume increase, and it was more prominent than that of weight gain among the children with SAM by WHZ and MUAC over all the restoring period. Based on this we made a conjecture about dominant fat mass gain over the period of CMAM program. Also, considering initial weight gain could be ascribed to fat mass increase, the current discharge criteria would leave the malnourishe…
An Integrative Assessment of the Psychophysiologic Alterations in Young Women With Recurrent Major Depressive Disorder
Objective Alterations in neuroelectrical activities coincide with major depressive disorder (MDD). This study examines the pattern of cerebral activity and cardiac autonomic parameters of euthymic women with recurrent MDD. Methods Resting electroencephalograms and electrocardiograms were recorded from 20 women with MDD receiving escitalopram and 40 matched and healthy women. We computed frontal alpha asymmetry to evaluate the interhemispheric bal…
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An Integrative Assessment of the Psychophysiologic Alterations in Young Women With Recurrent Major Depressive Disorder
Objective Alterations in neuroelectrical activities coincide with major depressive disorder (MDD). This study examines the pattern of cerebral activity and cardiac autonomic parameters of euthymic women with recurrent MDD. Methods Resting electroencephalograms and electrocardiograms were recorded from 20 women with MDD receiving escitalopram and 40 matched and healthy women. We computed frontal alpha asymmetry to evaluate the interhemispheric bal…
Do we need to reconsider the CMAM admission and discharge criteria?; an analysis of CMAM data in South Sudan
The relative velocity of MUAC 3 gain was suggested as a proxy measure for volume increase, and it was more prominent than that of weight gain among the children with SAM by WHZ and MUAC over all the restoring period. Based on this we made a conjecture about dominant fat mass gain over the period of CMAM program. Also, considering initial weight gain could be ascribed to fat mass increase, the current discharge criteria would leave the malnourishe…
A Deep Learning Algorithm to Predict Hazardous Drinkers and the Severity of Alcohol-Related Problems Using K-NHANES
Purpose: The number of patients with alcohol-related problems is steadily increasing. A large-scale survey of alcohol-related problems has been conducted. However, studies that predict hazardous drinkers and identify which factors contribute to the prediction are limited. Thus, the purpose of this study was to predict hazardous drinkers and the severity of alcohol-related problems of patients using a deep learning algorithm based on a large-scale…
Estimation of Undetected Asymptomatic Covid-19 Cases in South Korea Using a Probabilistic Model
Increasing evidence shows that many infections of COVID-19 are asymptomatic, becoming a global challenge, since asymptomatic infections have the same infectivity as symptomatic infections. We developed a probabilistic model for estimating the proportion of undetected asymptomatic COVID-19 patients in the country. We considered two scenarios: one is conservative and the other is nonconservative. By combining the above two scenarios, we gave an int…
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…
Machine learning models to predict the maximum severity of Covid-19 based on initial hospitalization record
Background: As the worldwide spread of coronavirus disease 2019 (COVID-19) continues for a long time, early prediction of the maximum severity is required for effective treatment of each patient. Objective: This study aimed to develop predictive models for the maximum severity of hospitalized COVID-19 patients using artificial intelligence (AI)/machine learning (ML) algorithms. Methods: The medical records of 2,263 COVID-19 patients admitted to 1…
A statistical look at the Covid-19 vaccine development and vaccine policies
The global outbreak of COVID-19 caused by the SARS-CoV-2 virus elicited immense global interest in the development and distribution of safe COVID-19 vaccines by various governments and researchers, capable of stopping the spread of COVID-19 disease. After COVID-19 was declared a global pandemic, several vaccines have been developed for emergency use authorization. The accelerated development of the vaccines was attributed to many factors but main…
Statistical modeling of health space based on metabolic stress and oxidative stress scores
These validation studies using two independent datasets successfully demonstrated the usefulness of the proposed HS
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…
Medicine (11 works) · COVID-19 epidemiological studies (6 works) · Internal Medicine (6 works) · Pandemic (6 works) · Environmental health (5 works) · Outbreak (5 works) · Population (5 works) · Virology (5 works) · Computer Science (4 works) · Disease (4 works)