AIMC Topic: Republic of Korea
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Machine learning for prediction of septic shock at initial triage in emergency department.
Journal of critical care
Oct 22, 2019
BACKGROUND: We hypothesized utilizing machine learning (ML) algorithms for screening septic shock in ED would provide better accuracy than qSOFA or MEWS.
Depression Prediction by Using Ecological Momentary Assessment, Actiwatch Data, and Machine Learning: Observational Study on Older Adults Living Alone.
JMIR mHealth and uHealth
Oct 16, 2019
BACKGROUND: Although geriatric depression is prevalent, diagnosis using self-reporting instruments has limitations when measuring the depressed mood of older adults in a community setting. Ecological momentary assessment (EMA) by using wearable devic...
Delineation of high resolution climate regions over the Korean Peninsula using machine learning approaches.
PloS one
Oct 10, 2019
In this research, climate classification maps over the Korean Peninsula at 1 km resolution were generated using the satellite-based climatic variables of monthly temperature and precipitation based on machine learning approaches. Random forest (RF), ...
Machine learning based risk prediction model for asymptomatic individuals who underwent coronary artery calcium score: Comparison with traditional risk prediction approaches.
Journal of cardiovascular computed tomography
Sep 23, 2019
BACKGROUND: Machine learning (ML) is a computer algorithm used to identify patterns for prediction in various tasks, and ML methods have been beneficial for developing prediction models when applied to heterogeneous and large datasets. We aim to exam...
Retrospective Studies
Republic of Korea
Female
Risk Factors
Adult
Machine Learning
Decision Support Techniques
Databases, Factual
Prognosis
Health Status
Predictive Value of Tests
Coronary Angiography
Registries
Coronary Artery Disease
Male
Middle Aged
Risk Assessment
Time Factors
Humans
Vascular Calcification
Asymptomatic Diseases
A deep learning model for real-time mortality prediction in critically ill children.
Critical care (London, England)
Aug 14, 2019
BACKGROUND: The rapid development in big data analytics and the data-rich environment of intensive care units together provide unprecedented opportunities for medical breakthroughs in the field of critical care. We developed and validated a machine l...
Development of interval-valued fuzzy GRA with SERVPERF based on subjective and objective weights for evaluation of airline service quality: A case study of Korea low-cost carriers.
PloS one
Aug 6, 2019
As the airline industry has become ever-more competitive and profitability more tenuous, airline service quality management has grown more important to airlines. Although many studies have focused on the evaluation of airline service quality, some co...
Community-dwelling older adults' needs and acceptance regarding the use of robot technology to assist with daily living performance.
BMC geriatrics
Aug 5, 2019
BACKGROUND: The rate of aging in Korea is extremely fast compared to major countries. We examined the key demands of community-dwelling older adults with regard to Connected Active Space technology, which provides tailored assistance with daily livin...
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...
Comparisons among Machine Learning Models for the Prediction of Hypercholestrolemia Associated with Exposure to Lead, Mercury, and Cadmium.
International journal of environmental research and public health
Jul 25, 2019
Lead, mercury, and cadmium are common environmental pollutants in industrialized countries, but their combined impact on hypercholesterolemia (HC) is poorly understood. The aim of this study was to compare the performance of various machine learning ...
Identifying depression in the National Health and Nutrition Examination Survey data using a deep learning algorithm.
Journal of affective disorders
Jul 4, 2019
BACKGROUND: As depression is the leading cause of disability worldwide, large-scale surveys have been conducted to establish the occurrence and risk factors of depression. However, accurately estimating epidemiological factors leading up to depressio...
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