AIMC Topic: Republic of Korea

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BERT and BERTopic for screening clinical depression on open-ended text messages collected through a mobile application from older adults.

BMC public health
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
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
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
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
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
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...

Artificial intelligence applied to electrocardiogram to rule out acute myocardial infarction: the ROMIAE multicentre study.

European heart journal
BACKGROUND AND AIMS: Emerging evidence supports artificial intelligence-enhanced electrocardiogram (AI-ECG) for detecting acute myocardial infarction (AMI), but real-world validation is needed. The aim of this study was to evaluate the performance of...

Deep learning health space model for ordered responses.

BMC medical informatics and decision making
BACKGROUND: As personalized medicine becomes more prevalent, the objective measurement and visualization of an individual's health status are becoming increasingly crucial. However, as the dimensions of data collected from each individual increase, t...

Optimizing Automated KCD Coding: A Retrieval-Verification Approach.

Studies in health technology and informatics
This study proposes a two-step Retrieval-Verification system for automating the assignment of Korean Standard Classification of Diseases (KCD) codes to free-text diagnoses. The system uses SapBERT-XLMR for initial retrieval, followed by Llama 3.1 for...

Comparative Analysis of ChatGPT-4 for Automated Mapping of Local Medical Terminologies to SNOMED CT.

Studies in health technology and informatics
Standardizing medical terminology is critical for healthcare informatics, particularly for improving data interoperability and patient management systems. This study evaluated four distinct GPT-4-based approaches for mapping local medical terminologi...