AIMC Topic: Republic of Korea

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Algal Bloom Prediction Using Extreme Learning Machine Models at Artificial Weirs in the Nakdong River, Korea.

International journal of environmental research and public health Sep 21, 2018
In this study, we design an intelligent model to predict chlorophyll-a concentration, which is the primary indicator of algal blooms, using extreme learning machine (ELM) models. Modeling algal blooms is important for environmental management and eco...
Neural Networks, Computer Rivers Harmful Algal Bloom Chlorophyll Machine Learning Republic of Korea Environmental Monitoring
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A Novel Fundus Image Reading Tool for Efficient Generation of a Multi-dimensional Categorical Image Database for Machine Learning Algorithm Training.

Journal of Korean medical science Aug 8, 2018
BACKGROUND: We described a novel multi-step retinal fundus image reading system for providing high-quality large data for machine learning algorithms, and assessed the grader variability in the large-scale dataset generated with this system.
Humans Republic of Korea Machine Learning Fundus Oculi Databases, Factual Retina
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Conditional random fields for clinical named entity recognition: A comparative study using Korean clinical texts.

Computers in biology and medicine Aug 1, 2018
BACKGROUND: This study demonstrates clinical named entity recognition (NER) methods on the clinical texts of rheumatism patients in South Korea. Despite the recent increase in the adoption rate of the electronic health record (EHR) system in global h...
Data Mining Medical Informatics Humans Republic of Korea Natural Language Processing
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Predicting Infectious Disease Using Deep Learning and Big Data.

International journal of environmental research and public health Jul 27, 2018
Infectious disease occurs when a person is infected by a pathogen from another person or an animal. It is a problem that causes harm at both individual and macro scales. The Korea Center for Disease Control (KCDC) operates a surveillance system to mi...
Humans Algorithms Republic of Korea Deep Learning Forecasting Models, Theoretical Communicable Diseases
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Four Major South Korea's Rivers Using Deep Learning Models.

International journal of environmental research and public health Jun 24, 2018
Harmful algal blooms are an annual phenomenon that cause environmental damage, economic losses, and disease outbreaks. A fundamental solution to this problem is still lacking, thus, the best option for counteracting the effects of algal blooms is to ...
Republic of Korea Deep Learning Harmful Algal Bloom Models, Biological Water Quality Rivers
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Characterization of hidden rules linking symptoms and selection of acupoint using an artificial neural network model.

Frontiers of medicine Apr 12, 2018
Comprehension of the medical diagnoses of doctors and treatment of diseases is important to understand the underlying principle in selecting appropriate acupoints. The pattern recognition process that pertains to symptoms and diseases and informs acu...
Acupuncture Points Syndrome Acupuncture Therapy Humans Neural Networks, Computer Republic of Korea
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Deep ECGNet: An Optimal Deep Learning Framework for Monitoring Mental Stress Using Ultra Short-Term ECG Signals.

Telemedicine journal and e-health : the official journal of the American Telemedicine Association Feb 8, 2018
BACKGROUND: Stress recognition using electrocardiogram (ECG) signals requires the intractable long-term heart rate variability (HRV) parameter extraction process. This study proposes a novel deep learning framework to recognize the stressful states, ...
Electrocardiography Heart Rate Belgium Deep Learning Stress, Psychological Image Processing, Computer-Assisted Adult Male Humans Neural Networks, Computer Republic of Korea Young Adult
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Effect of a short-term physical activity intervention on liver fat content in obese children.

Applied physiology, nutrition, and metabolism = Physiologie appliquee, nutrition et metabolisme Dec 20, 2017
Nonalcoholic fatty liver disease is the most common chronic liver disease and can present with advanced fibrosis or nonalcoholic steatohepatitis. The purpose of this study was to investigate the effect of a 7-day intense physical activity interventio...
Age Factors Liver Lipid Metabolism Weight Loss Pediatric Obesity Aspartate Aminotransferases Insulin Body Mass Index Time Factors Child Insulin Resistance Republic of Korea Treatment Outcome Female Non-alcoholic Fatty Liver Disease Humans Male Exercise Therapy Biomarkers Adiposity
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Predictability of machine learning techniques to forecast the trends of market index prices: Hypothesis testing for the Korean stock markets.

PloS one Nov 14, 2017
The prediction of the trends of stocks and index prices is one of the important issues to market participants. Investors have set trading or fiscal strategies based on the trends, and considerable research in various academic fields has been studied ...
Models, Economic Commerce Republic of Korea Support Vector Machine Machine Learning Forecasting
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Neural Network-Based Coronary Heart Disease Risk Prediction Using Feature Correlation Analysis.

Journal of healthcare engineering Sep 6, 2017
BACKGROUND: Of the machine learning techniques used in predicting coronary heart disease (CHD), neural network (NN) is popularly used to improve performance accuracy.
Neural Networks, Computer Databases, Factual Republic of Korea Female Risk Factors Aged Humans Nutrition Surveys Coronary Artery Disease Middle Aged Aged, 80 and over Risk Assessment Adult ROC Curve Male
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