AIMC Topic: Republic of Korea
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Confidence-linked and uncertainty-based staged framework for phenotype validation using large language models.
Journal of the American Medical Informatics Association : JAMIA
Aug 1, 2025
OBJECTIVES: This study develops and validates the confidence-linked and uncertainty-based staged (CLUES) framework by integrating large language models (LLMs) with uncertainty quantification to assist manual chart review while ensuring reliability th...
Comparative Analysis of Large Language Models for Answering Cancer-Related Questions in Korean.
Yonsei medical journal
Jul 1, 2025
PURPOSE: Large language models (LLMs) have shown potential in medicine, transforming patient education, clinical decision support, and medical research. However, the effectiveness of LLMs in providing accurate medical information, particularly in non...
Machine learning-based prediction of ambient CO and CH concentrations with high temporal resolution in Seoul metropolitan area.
Environmental pollution (Barking, Essex : 1987)
Jul 1, 2025
Machine learning has the potential to support the growing need for high-resolution greenhouse gas monitoring in urban and industrial environments, where deploying extensive sensor networks is often limited by cost and operational challenges. This stu...
Deep learning-based forecasting of daily maximum ozone levels and assessment of socioeconomic and health impacts in South Korea.
The Science of the total environment
Jun 25, 2025
Accurate forecasting of ground-level ozone (O) is essential for assessing its public health and socioeconomic impacts. This study evaluates the performance of three deep learning models-Deep Convolutional Neural Networks (Deep-CNN), Long Short-Term M...
BERT and BERTopic for screening clinical depression on open-ended text messages collected through a mobile application from older adults.
BMC public health
Jun 10, 2025
BACKGROUND: Despite the high suicide rate in South Korea, older adults are reluctant to see a psychiatrist. Recently, text mining has gained popularity to detect depression in social media posts, but older adults rarely use social media. However, mor...
Segmentation of Leukoaraiosis on Noncontrast Head CT Using CT-MRI Paired Data Without Human Annotation.
Brain and behavior
Jun 1, 2025
OBJECTIVE: Evaluating leukoaraiosis (LA) on CT is challenging due to its low contrast and similarity to parenchymal gliosis. We developed and validated a deep learning algorithm for LA segmentation using CT-MRIFLAIR paired data from a multicenter Kor...
Explainable AI-based risk assessment for pluvial floods over South Korea.
Journal of environmental management
Jun 1, 2025
Analytic Hierarchy Process (AHP) of pluvial flood risk assessment has been widely used, incorporating multiple assessment indices. However, uncertainty assessment of expert judgement-based flood risk remains limited. This study proposes a Machine Lea...
Improved prediction of chlorophyll-a concentrations using advancing graph neural network variants.
The Science of the total environment
Jun 1, 2025
Accurate estimation of harmful algal blooms is essential for protecting surface water. Chlorophyll-a (Chl-a), commonly used as a proxy for estimating algal concentration, is influenced by a broad range of weather and physicochemical factors that oper...
Predicting cognitive frailty in community-dwelling older adults: a machine learning approach based on multidomain risk factors.
Scientific reports
May 26, 2025
Cognitive frailty (CF), a clinical syndrome involving both physical frailty (PF) and impaired cognition (IC), is associated with adverse health outcomes in older adults. This study aimed to identify key predictors of CF and develop a machine learning...
Machine learning-based analysis on factors influencing blood heavy metal concentrations in the Korean CHildren's ENvironmental health Study (Ko-CHENS).
The Science of the total environment
May 25, 2025
Heavy metal concentration in pregnant women affects neurocognitive and behavioral development of their infants and children. The majority of existing research focusing on pregnant women's heavy metal concentration has considered individual environmen...
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