AIMC Topic: Seoul

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Image-based ECG analyzing deep-learning algorithm to predict biological age and mortality risks: interethnic validation.

Journal of cardiovascular medicine (Hagerstown, Md.) Sep 12, 2024
BACKGROUND: Cardiovascular risk assessment is a critical component of healthcare, guiding preventive and therapeutic strategies. In this study, we developed and evaluated an image-based electrocardiogram (ECG) analyzing an artificial intelligence (AI...
Predictive Value of Tests Heart Disease Risk Factors Seoul Risk Assessment Deep Learning Electrocardiography Age Factors Reproducibility of Results Aged Aged, 80 and over Young Adult Adult Male Cardiovascular Diseases Middle Aged Humans Prognosis Female
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Examining the Relationship between Land Use/Land Cover (LULC) and Land Surface Temperature (LST) Using Explainable Artificial Intelligence (XAI) Models: A Case Study of Seoul, South Korea.

International journal of environmental research and public health Nov 29, 2022
Understanding the relationship between land use/land cover (LULC) and land surface temperature (LST) has long been an area of interest in urban and environmental study fields. To examine this, existing studies have utilized both white-box and black-b...
Seoul Artificial Intelligence Temperature Environmental Monitoring City Planning
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Interpretable machine learning approach to analyze the effects of landscape and meteorological factors on mosquito occurrences in Seoul, South Korea.

Environmental science and pollution research international Jul 28, 2022
Mosquitoes are the underlying cause of various public health and economic problems. In this study, patterns of mosquito occurrence were analyzed based on landscape and meteorological factors in the metropolitan city of Seoul. We evaluated the influen...
Animals Cities Seoul Meteorological Concepts Machine Learning Republic of Korea
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Extracting Structured Genotype Information from Free-Text HLA Reports Using a Rule-Based Approach.

Journal of Korean medical science Mar 30, 2020
BACKGROUND: Human leukocyte antigen (HLA) typing is important for transplant patients to prevent a severe mismatch reaction, and the result can also support the diagnosis of various disease or prediction of drug side effects. However, such secondary ...
Natural Language Processing HLA Antigens Information Storage and Retrieval Seoul Humans Algorithms Electronic Health Records Genotype Data Warehousing Histocompatibility Testing
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Improved Accuracy in Optical Diagnosis of Colorectal Polyps Using Convolutional Neural Networks with Visual Explanations.

Gastroenterology Feb 29, 2020
BACKGROUND & AIMS: Narrow-band imaging (NBI) can be used to determine whether colorectal polyps are adenomatous or hyperplastic. We investigated whether an artificial intelligence (AI) system can increase the accuracy of characterizations of polyps b...
Colonic Polyps Image Interpretation, Computer-Assisted Observer Variation Hyperplasia Visual Perception Deep Learning Seoul Clinical Competence Adenomatous Polyps Predictive Value of Tests Humans Narrow Band Imaging Colorectal Neoplasms Workflow Reproducibility of Results Colonoscopy Diagnosis, Computer-Assisted
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Mapping urban air quality using mobile sampling with low-cost sensors and machine learning in Seoul, South Korea.

Environment international Jul 27, 2019
Recent studies have demonstrated that mobile sampling can improve the spatial granularity of land use regression (LUR) models. Mobile sampling campaigns deploying low-cost (<$300) air quality sensors could potentially offer an inexpensive and practic...
Environmental Monitoring Air Pollutants Air Pollution Particulate Matter Linear Models Seoul Machine Learning Humans Republic of Korea Mobile Applications Urban Population
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Deep Learning Approaches to Detect Atrial Fibrillation Using Photoplethysmographic Signals: Algorithms Development Study.

JMIR mHealth and uHealth Jun 6, 2019
BACKGROUND: Wearable devices have evolved as screening tools for atrial fibrillation (AF). A photoplethysmographic (PPG) AF detection algorithm was developed and applied to a convenient smartphone-based device with good accuracy. However, patients wi...
Female Reproducibility of Results Aged Male Humans Sensitivity and Specificity Middle Aged Electrocardiography Algorithms Deep Learning Atrial Fibrillation Photoplethysmography Prospective Studies Seoul
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An Algorithm Based on Deep Learning for Predicting In-Hospital Cardiac Arrest.

Journal of the American Heart Association Jun 26, 2018
BACKGROUND: In-hospital cardiac arrest is a major burden to public health, which affects patient safety. Although traditional track-and-trigger systems are used to predict cardiac arrest early, they have limitations, with low sensitivity and high fal...
Seoul Reproducibility of Results Early Diagnosis Risk Factors Vital Signs Aged Heart Arrest Adult Decision Support Techniques Resuscitation Deep Learning Humans Male Prognosis Time Factors Middle Aged Retrospective Studies Inpatients Risk Assessment Female Predictive Value of Tests Diagnosis, Computer-Assisted
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Evaluating the predictability of PM grades in Seoul, Korea using a neural network model based on synoptic patterns.

Environmental pollution (Barking, Essex : 1987) Sep 6, 2016
As of November 2014, the Korean Ministry of Environment (KME) has been forecasting the concentration of particulate matter with diameters ≤ 10 μm (PM) classified into four grades: low (PM ≤ 30 μg m), moderate (30 < PM ≤ 80 μg m), high (80 < PM ≤ 150 ...
Environmental Monitoring Temperature Seasons Neural Networks, Computer Particle Size Meteorology Wind Forecasting Air Pollutants Seoul China Republic of Korea Particulate Matter Models, Theoretical
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Machine learning-based prediction of ambient CO and CH concentrations with high temporal resolution in Seoul metropolitan area.

Environmental pollution (Barking, Essex : 1987) Jul 1, 2025
Machine learning has the potential to support the growing need for high-resolution greenhouse gas monitoring in urban and industrial environments, where deploying extensive sensor networks is often limited by cost and operational challenges. This stu...
Machine Learning Methane Carbon Dioxide Greenhouse Gases Seoul Republic of Korea Environmental Monitoring Air Pollutants Air Pollution
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