AI Medical Compendium Topic

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Republic of Korea

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Predicting Infectious Disease Using Deep Learning and Big Data.

International journal of environmental research and public health
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...

Four Major South Korea's Rivers Using Deep Learning Models.

International journal of environmental research and public health
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 ...

Characterization of hidden rules linking symptoms and selection of acupoint using an artificial neural network model.

Frontiers of medicine
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...

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
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, ...

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
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...

Predictability of machine learning techniques to forecast the trends of market index prices: Hypothesis testing for the Korean stock markets.

PloS one
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 ...

Neural Network-Based Coronary Heart Disease Risk Prediction Using Feature Correlation Analysis.

Journal of healthcare engineering
BACKGROUND: Of the machine learning techniques used in predicting coronary heart disease (CHD), neural network (NN) is popularly used to improve performance accuracy.

Development and assessment of a lysophospholipid-based deep learning model to discriminate geographical origins of white rice.

Scientific reports
Geographical origin determination of white rice has become the major issue of food industry. However, there is still lack of a high-throughput method for rapidly and reproducibly differentiating the geographical origins of commercial white rice. In t...

Large-scale machine learning of media outlets for understanding public reactions to nation-wide viral infection outbreaks.

Methods (San Diego, Calif.)
From May to July 2015, there was a nation-wide outbreak of Middle East respiratory syndrome (MERS) in Korea. MERS is caused by MERS-CoV, an enveloped, positive-sense, single-stranded RNA virus belonging to the family Coronaviridae. Despite expert opi...

Evaluating the predictability of PM grades in Seoul, Korea using a neural network model based on synoptic patterns.

Environmental pollution (Barking, Essex : 1987)
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 ...