AIMC Topic: Republic of Korea

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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
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
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...

Prediction models for high risk of suicide in Korean adolescents using machine learning techniques.

PloS one
OBJECTIVE: Suicide in adolescents is a major problem worldwide and previous history of suicide ideation and attempt represents the strongest predictors of future suicidal behavior. The aim of this study was to develop prediction model to identify Kor...

Comparison of robot-assisted modified radical neck dissection using a bilateral axillary breast approach with a conventional open procedure after propensity score matching.

Surgical endoscopy
BACKGROUND: There is ongoing debate about whether or not robot-assisted thyroidectomy is appropriate for modified radical neck dissection (MRND). The purpose of this study was to compare the surgical outcomes of robot-assisted MRND with those of a co...

Research on Patient Satisfaction of Robotic Telerounding: A Pilot Study in a Korean Population.

Urology
OBJECTIVES: To evaluate the efficacy and functionality of robotic telerounding among Korean patients using the RP-7 robot system and a questionnaire survey comparing the results of robotic telerounding and standard rounding in Korean patients.

Hybrid multivariate pattern analysis combined with extreme learning machine for Alzheimer's dementia diagnosis using multi-measure rs-fMRI spatial patterns.

PloS one
BACKGROUND: Early diagnosis of Alzheimer's disease (AD) and Mild Cognitive Impairment (MCI) is essential for timely treatment. Machine learning and multivariate pattern analysis (MVPA) for the diagnosis of brain disorders are explicitly attracting at...

Association of time to colonoscopy after a positive fecal test result and fecal hemoglobin concentration with risk of advanced colorectal neoplasia.

Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver
BACKGROUND: We evaluated the risk of advanced colorectal neoplasia (ACRN) and colorectal cancer (CRC) according to time to colonoscopy after positive fecal immunochemical test (FIT), fecal hemoglobin concentration, and combination of both.

Sequential prediction of quantitative health risk assessment for the fine particulate matter in an underground facility using deep recurrent neural networks.

Ecotoxicology and environmental safety
Particulate matter with aerodynamic diameter less than 2.5 µm (PM) in indoor public spaces such as subway stations, has represented a major public health concern; however, forecasting future sequences of quantitative health risk is an effective metho...