AIMC Topic: Republic of Korea

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Defining heterogeneity of epicardial functional stenosis with low coronary flow reserve by unsupervised machine learning.

Heart and vessels Jun 6, 2020
Low CFR is associated with poor prognosis, whereas it is a heterogeneous condition according to the actual coronary flow, such as high resting or low hyperemic coronary flow, which should have different physiological traits and clinical implications....
Male Middle Aged Severity of Illness Index Diagnosis, Computer-Assisted Cluster Analysis Humans Blood Flow Velocity Prognosis Cardiac Catheterization Unsupervised Machine Learning Republic of Korea Predictive Value of Tests Coronary Stenosis Female Registries Fractional Flow Reserve, Myocardial Aged Japan Hyperemia Spain
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Assessing the biochemical oxygen demand using neural networks and ensemble tree approaches in South Korea.

Journal of environmental management Jun 5, 2020
The biochemical oxygen demand (BOD), one of widely utilized variables for water quality assessment, is metric for the ecological division in rivers. Since the traditional approach to predict BOD is time-consuming and inaccurate due to inconstancies i...
Neural Networks, Computer Oxygen Republic of Korea Environmental Monitoring Water Quality Rivers Biological Oxygen Demand Analysis
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What are the main patient safety concerns of healthcare stakeholders: a mixed-method study of Web-based text.

International journal of medical informatics May 4, 2020
OBJECTIVES: Various healthcare stakeholders define quality of care in different ways. Public policy could advocate all these concerns. This study was conducted to identify the main themes on patient safety of stakeholders expressed before and after t...
Humans Research Design Patient Safety Republic of Korea Quality Improvement Government Hospitals Longitudinal Studies Natural Language Processing Internet Health Services
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Prediction of the Mortality Risk in Peritoneal Dialysis Patients using Machine Learning Models: A Nation-wide Prospective Cohort in Korea.

Scientific reports May 4, 2020
Herein, we aim to assess mortality risk prediction in peritoneal dialysis patients using machine-learning algorithms for proper prognosis prediction. A total of 1,730 peritoneal dialysis patients in the CRC for ESRD prospective cohort from 2008 to 20...
Humans Machine Learning Prospective Studies Mortality Peritoneal Dialysis Adult Male Middle Aged Republic of Korea Predictive Value of Tests Female Models, Biological Risk Factors Aged
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A double-hit of stress and low-grade inflammation on functional brain network mediates posttraumatic stress symptoms.

Nature communications Apr 20, 2020
Growing evidence indicates a reciprocal relationship between low-grade systemic inflammation and stress exposure towards increased vulnerability to neuropsychiatric disorders, including posttraumatic stress disorder (PTSD). However, the neural correl...
Nerve Net Stress Disorders, Post-Traumatic Inflammation Magnetic Resonance Imaging Neural Pathways Humans Neural Networks, Computer Cytokines Brain Republic of Korea Female Young Adult Adult Male
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Association of Cardiovascular Mortality and Deep Learning-Funduscopic Atherosclerosis Score derived from Retinal Fundus Images.

American journal of ophthalmology Mar 25, 2020
PURPOSE: The prediction of atherosclerosis using retinal fundus images and deep learning has not been shown possible. The purpose of this study was to develop a deep learning model which predicted atherosclerosis by using retinal fundus images and to...
Ophthalmoscopy Republic of Korea Predictive Value of Tests Female Atherosclerosis Risk Factors Fundus Oculi Aged Humans Retina Aged, 80 and over Prognosis Carotid Arteries Risk Assessment Adult Retrospective Studies Deep Learning Survival Rate Ultrasonography Male Follow-Up Studies Cardiovascular Diseases Middle Aged
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Deep Learning-Based Algorithm for Detecting Aortic Stenosis Using Electrocardiography.

Journal of the American Heart Association Mar 21, 2020
Background Severe, symptomatic aortic stenosis (AS) is associated with poor prognoses. However, early detection of AS is difficult because of the long asymptomatic period experienced by many patients, during which screening tools are ineffective. The...
Severity of Illness Index Humans Predictive Value of Tests Aged Deep Learning Retrospective Studies Signal Processing, Computer-Assisted Aged, 80 and over Electrocardiography Republic of Korea Early Diagnosis Male Aortic Valve Stenosis Female Middle Aged Reproducibility of Results Aortic Valve
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Artificial intelligence algorithm to predict the need for critical care in prehospital emergency medical services.

Scandinavian journal of trauma, resuscitation and emergency medicine Mar 4, 2020
BACKGROUND: In emergency medical services (EMSs), accurately predicting the severity of a patient's medical condition is important for the early identification of those who are vulnerable and at high-risk. In this study, we developed and validated an...
Triage Algorithms Emergency Service, Hospital Middle Aged Retrospective Studies Humans Deep Learning Critical Care Republic of Korea Artificial Intelligence Cohort Studies Female Emergency Medical Services Male
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Machine learning algorithm to predict mortality in patients undergoing continuous renal replacement therapy.

Critical care (London, England) Feb 6, 2020
BACKGROUND: Previous scoring models such as the Acute Physiologic Assessment and Chronic Health Evaluation II (APACHE II) and the Sequential Organ Failure Assessment (SOFA) scoring systems do not adequately predict mortality of patients undergoing co...
Algorithms Continuous Renal Replacement Therapy Acute Kidney Injury Republic of Korea Female Risk Factors Aged Aged, 80 and over Male Middle Aged Humans Machine Learning Organ Dysfunction Scores Severity of Illness Index Mortality ROC Curve Area Under Curve APACHE
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Predicting future onset of depression among community dwelling adults in the Republic of Korea using a machine learning algorithm.

Neuroscience letters Jan 31, 2020
Because depression has high prevalence and cause enduring disability, it is important to predict onset of depression among community dwelling adults. In this study, we aimed to build a machine learning-based predictive model for future onset of depre...
Depression Republic of Korea Humans Surveys and Questionnaires Female Longitudinal Studies Machine Learning Adult Independent Living Algorithms Male Forecasting Middle Aged
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