Hahn Yi
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View article: Artificial Intelligence Models May Aid in Predicting Lymph Node Metastasis in Patients with T1 Colorectal Cancer
Artificial Intelligence Models May Aid in Predicting Lymph Node Metastasis in Patients with T1 Colorectal Cancer Open
AI models trained on the basis of endoscopic findings and pathological features performed well in predicting LNM in patients with T1 CRC regardless of tumor location and initial treatment method.
View article: Machine Learning Algorithms Predict Successful Weaning From Mechanical Ventilation Before Intubation: Retrospective Analysis From the Medical Information Mart for Intensive Care IV Database
Machine Learning Algorithms Predict Successful Weaning From Mechanical Ventilation Before Intubation: Retrospective Analysis From the Medical Information Mart for Intensive Care IV Database Open
Background The prediction of successful weaning from mechanical ventilation (MV) in advance of intubation can facilitate discussions regarding end-of-life care before unnecessary intubation. Objective We aimed to develop a machine learning…
View article: Machine Learning Algorithms Predict Successful Weaning From Mechanical Ventilation Before Intubation: Retrospective Analysis From the Medical Information Mart for Intensive Care IV Database (Preprint)
Machine Learning Algorithms Predict Successful Weaning From Mechanical Ventilation Before Intubation: Retrospective Analysis From the Medical Information Mart for Intensive Care IV Database (Preprint) Open
BACKGROUND The prediction of successful weaning from mechanical ventilation (MV) in advance of intubation can facilitate discussions regarding end-of-life care before unnecessary intubation. OBJECTIVE We aimed to develop a machine learn…
View article: Machine Learning Algorithms Predict Successful Weaning from Mechanical Ventilation Before Intubation
Machine Learning Algorithms Predict Successful Weaning from Mechanical Ventilation Before Intubation Open
Prediction of successful weaning from mechanical ventilation in advance to intubation can facilitate discussions regarding end-of-life care before unnecessary intubation. In this context, we aimed to develop a machine-learning-based model …
View article: Air Pollution and Subarachnoid Hemorrhage Mortality: A Stronger Association in Women than in Men
Air Pollution and Subarachnoid Hemorrhage Mortality: A Stronger Association in Women than in Men Open
View article: Early Identification of Resuscitated Patients with a Significant Coronary Disease in Out-of-Hospital Cardiac Arrest Survivors without ST-Segment Elevation
Early Identification of Resuscitated Patients with a Significant Coronary Disease in Out-of-Hospital Cardiac Arrest Survivors without ST-Segment Elevation Open
This study aimed to develop a machine learning (ML)-based model for identifying patients who had a significant coronary artery disease among out-of-hospital cardiac arrest (OHCA) survivors without ST-segment elevation (STE). This multicent…
View article: Prediction of Neurologically Intact Survival in Cardiac Arrest Patients without Pre-Hospital Return of Spontaneous Circulation: Machine Learning Approach
Prediction of Neurologically Intact Survival in Cardiac Arrest Patients without Pre-Hospital Return of Spontaneous Circulation: Machine Learning Approach Open
Current multimodal approaches for the prognostication of out-of-hospital cardiac arrest (OHCA) are based mainly on the prediction of poor neurological outcomes; however, it is challenging to identify patients expected to have a favorable o…
View article: Association between long-term exposure to air pollutants and cardiopulmonary mortality rates in South Korea
Association between long-term exposure to air pollutants and cardiopulmonary mortality rates in South Korea Open
Background The association between long-term exposure to air pollutants, including nitrogen dioxide (NO 2 ), carbon monoxide (CO), sulfur dioxide (SO 2 ), ozone (O 3 ), and particulate matter 10 μm or less in diameter (PM 10 ), and mortali…
View article: Association between long-term exposure to air pollutants and cardiopulmonary mortality rates in South Korea
Association between long-term exposure to air pollutants and cardiopulmonary mortality rates in South Korea Open
Background: The association between long-term exposure to air pollutants, including nitrogen dioxide (NO2), carbon monoxide (CO), sulfur dioxide (SO2), ozone (O3), and particulate matter 10 μm or less in di…
View article: Association between long-term exposure to air pollutants and cardiopulmonary mortality rates in South Korea
Association between long-term exposure to air pollutants and cardiopulmonary mortality rates in South Korea Open
Background : The association between long-term exposure to air pollutants, including nitrogen dioxide (NO 2 ), carbon monoxide (CO), sulfur dioxide (SO 2 ), ozone (O 3 ), and particulate matter 10 μm or less in diameter (PM 10 ), and morta…
View article: Prediction of Adverse Events in Stable Non-Variceal Gastrointestinal Bleeding Using Machine Learning
Prediction of Adverse Events in Stable Non-Variceal Gastrointestinal Bleeding Using Machine Learning Open
Clinical risk-scoring systems are important for identifying patients with upper gastrointestinal bleeding (UGIB) who are at a high risk of hemodynamic instability. We developed an algorithm that predicts adverse events in patients with ini…
View article: Association between long-term exposure to air pollutants and cardiopulmonary mortality rates in South Korea
Association between long-term exposure to air pollutants and cardiopulmonary mortality rates in South Korea Open
Background: The association between long-term exposure to air pollutants, including nitrogen dioxide (NO2), carbon monoxide (CO), sulfur dioxide (SO2), ozone (O3), and particulate matter 10 μm or less in di…
View article: Impact of air pollution on breast cancer incidence and mortality: a nationwide analysis in South Korea
Impact of air pollution on breast cancer incidence and mortality: a nationwide analysis in South Korea Open
Breast cancer is one of the major female health problems worldwide. Although there is growing evidence indicating that air pollution increases the risk of breast cancer, there is still inconsistency among previous studies. Unlike the previ…
View article: Association between long-term exposure to ambient air pollutants and mortality rates because of circulatory and respiratory diseases in South Korea
Association between long-term exposure to ambient air pollutants and mortality rates because of circulatory and respiratory diseases in South Korea Open
Background : Associations between long-term exposure to common air pollutants including nitrogen dioxide, carbon monoxide, sulfur dioxide (SO 2 ), ozone, and particulate matter (PM 10 ) and health consequences have been studied. We investi…
View article: Age and sex subgroups vulnerable to copycat suicide: evaluation of nationwide data in South Korea
Age and sex subgroups vulnerable to copycat suicide: evaluation of nationwide data in South Korea Open
View article: Detecting Variability in Massive Astronomical Time-series Data. III. Variable Candidates in the SuperWASP DR1 Found by Multiple Clustering Algorithms and a Consensus Clustering Method
Detecting Variability in Massive Astronomical Time-series Data. III. Variable Candidates in the SuperWASP DR1 Found by Multiple Clustering Algorithms and a Consensus Clustering Method Open
We determine candidate variable sources in the SuperWASP Data Release 1 (DR1) using multiple clustering methods and identifying variable candidates as outliers from large clusters. We extract 15,788,814 light curves that have more than 15 …
View article: New Photometric Pipeline to Explore Temporal and Spatial Variability\n with KMTNet DEEP-South Observations
New Photometric Pipeline to Explore Temporal and Spatial Variability\n with KMTNet DEEP-South Observations Open
The DEEP-South photometric census of small Solar System bodies produces\nmassive time-series data of variable, transient or moving objects as a\nby-product. To fully investigate unexplored variable phenomena, we present an\napplication of …
View article: New Photometric Pipeline to Explore Temporal and Spatial Variability with KMTNet DEEP-South Observations
New Photometric Pipeline to Explore Temporal and Spatial Variability with KMTNet DEEP-South Observations Open
The DEEP-South photometric census of small Solar System bodies produces massive time-series data of variable, transient or moving objects as a by-product. To fully investigate unexplored variable phenomena, we present an application of mul…