A5028902149- ECG Monitoring and Analysis
- Geochemistry and Geologic Mapping
- Geological and Geochemical Analysis
- Cardiac Arrest and Resuscitation
- NF-κB Signaling Pathways
- Astro and Planetary Science
- Acute Myocardial Infarction Research
- Cardiovascular Function and Risk Factors
- Natural product bioactivities and synthesis
- Ultrasound in Clinical Applications
- Sepsis Diagnosis and Treatment
- Geological Modeling and Analysis
- Traumatic Brain Injury and Neurovascular Disturbances
- Immune Response and Inflammation
- earthquake and tectonic studies
- Cardiac Arrhythmias and Treatments
- Cardiovascular Issues in Pregnancy
- Atrial Fibrillation Management and Outcomes
- Cardiac Imaging and Diagnostics
- Heart Failure Treatment and Management
- Pharmacological Effects of Natural Compounds
- Metal Extraction and Bioleaching
- Thermal Regulation in Medicine
- Mineralogy and Gemology Studies
- Planetary Science and Exploration
Sejong Institute
2022-2025
Seoul National University Hospital
2013-2023
Bio-Medical Science (South Korea)
2023
Sejong General Hospital
2022
Weatherford College
2021
Keimyung University Dongsan Medical Center
2021
Keimyung University
2021
Seoul Metropolitan Government
2021
Seoul National University
2002-2021
Boramae Medical Center
2021
Background: We developed and validated an artificial intelligence (AI)-enabled smartwatch ECG to detect heart failure-reduced ejection fraction (HFrEF). Methods: This was a cohort study involving two hospitals (A B). the AI in steps. First, we model (ECGT2T) synthesize ten-lead from asynchronized 2-lead (Lead I II). ECGT2T is deep learning based on generative adversarial network, which translates source ECGs reference by styles of ECGs. For this, included adult patients aged ≥18 years...
Peripartum cardiomyopathy (PPCM) is a fatal maternal complication, with left ventricular systolic dysfunction (LVSD; Left ejection fraction 45% or less) occurring at the end of pregnancy in months following delivery. The scarcity screening tools for PPCM leads to delayed diagnosis and increases its mortality morbidity. We aim evaluate an electrocardiogram (ECG)-deep learning model (DLM) detecting peripartum period.For DLM development internal performance test LVSD, we obtained dataset...
Emerging evidence supports artificial intelligence-enhanced electrocardiogram (AI-ECG) for detecting acute myocardial infarction (AMI), but real-world validation is needed. The aim of this study was to evaluate the performance AI-ECG in AMI emergency department (ED). Rule-Out Myocardial Infarction using Artificial intelligence Electrocardiogram analysis (ROMIAE) a prospective cohort conducted Republic Korea from March 2022 October 2023, involving 18 university-level teaching hospitals. Adult...
Sn-W-Cu-Zn-Pb-Ag vein deposits in Japan, belonging to xenothermal class, occur or close proximity regions of rhyolitic (and andesitic) rocks intruded by granitic rocks. The are products the same igneous activities as intrusives. geologic age is late Cretaceous early Tertiary. Akenobe, Ikuno, and Tada mines western Japan Ashio mine eastern belong class.The fissures containing materials strike-slip faults tension cracks formed lateral pressure which caused folded structures each region. They...
Paroxysmal atrial fibrillation (AF) is a major potential cause of embolic stroke undetermined source (ESUS). However, identifying AF remains challenging because it occurs sporadically. Deep learning could be used to identify hidden based on the sinus rhythm (SR) electrocardiogram (ECG). We combined known risk factors and developed deep algorithm (DLA) for predicting optimize diagnostic performance in ESUS patients.A DLA was using SR 12-lead ECG with database consisting patients non-AF...
Abstract Aims Although evaluation of left ventricular ejection fraction (LVEF) is crucial for deciding the rate control strategy in patients with atrial fibrillation (AF), real-time assessment LVEF limited outpatient settings. We aimed to investigate performance artificial intelligence–based algorithms predicting LV systolic dysfunction (LVSD) AF and rapid response (RVR). Methods results This study an external validation a pre-existing deep learning algorithm based on residual neural network...
Electrocardiogram (ECG) synthesis is the area of research focused on generating realistic synthetic ECG signals for medical use without concerns over annotation costs or clinical data privacy restrictions. Traditional generation models consider a single lead and utilize GAN-based generative models. These can only generate samples require separate training each diagnosis class. The classes ECGs are insufficient to capture intricate differences between depending various features (e.g. patient...
To investigate whether regional cerebral oxygen saturation (rSO2) differs in out-of-hospital cardiac arrest (OHCA) survivors undergoing targeted temperature management (TTM) 36 °C versus 33 °C.A randomized clinical trial was conducted at intensive care units two referral hospitals. Fifty-seven comatose OHCA were into either a or group. Patients cooled and maintained an oesophageal of for 24 hours, rewarmed rate 0.25 °C/hour, <37.5 until 72 hours. During hours TTM, rSO2 continuously monitored...
Objectives Hyperchloraemia is associated with poor clinical outcomes in sepsis patients; however, this association not well studied for hypochloraemia. We investigated the prevalence of chloride imbalance and between hypochloraemia 28-day mortality ED patients septic shock. Methods A retrospective analysis data from 11 multicentre EDs Republic Korea prospectively collected October 2015 to April 2018 was performed. Initial levels were categorised as hypochloraemia, normochloraemia...
Although overt hyperthyroidism adversely affects a patient's prognosis, thyroid function tests (TFTs) are not routinely conducted. Furthermore, vague symptoms of often lead to being overlooked. An electrocardiogram (ECG) is commonly used screening test, and the association between ECG well known. However, it difficult for clinicians detect through subtle changes. For early detection hyperthyroidism, we aimed develop validate an electrocardiographic biomarker based on deep learning model...