AIMC Topic: Republic of Korea
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Automated Segmentation of MRI White Matter Hyperintensities in 8421 Patients with Acute Ischemic Stroke.
AJNR. American journal of neuroradiology
Dec 9, 2024
BACKGROUND AND PURPOSE: To date, only a few small studies have attempted deep learning-based automatic segmentation of white matter hyperintensity (WMH) lesions in patients with cerebral infarction; this issue is complicated because stroke-related le...
Application of machine learning for delirium prediction and analysis of associated factors in hospitalized COVID-19 patients: A comparative study using the Korean Multidisciplinary cohort for delirium prevention (KoMCoDe).
International journal of medical informatics
Dec 1, 2024
BACKGROUND: The incidence of delirium in hospitalized coronavirus disease 2019 (COVID-19) patients is linked to adverse health outcomes. Predicting the occurrence and risk factors of delirium is key to preventing its sudden onset.
Predictive model for abdominal liposuction volume in patients with obesity using machine learning in a longitudinal multi-center study in Korea.
Scientific reports
Nov 30, 2024
This study aimed to develop and validate a machine learning (ML)-based model for predicting liposuction volumes in patients with obesity. This study used longitudinal cohort data from 2018 to 2023 from five nationwide centers affiliated with 365MC Li...
Predicting early mortality in hemodialysis patients: a deep learning approach using a nationwide prospective cohort in South Korea.
Scientific reports
Nov 29, 2024
Early mortality after hemodialysis (HD) initiation significantly impacts the longevity of HD patients. This study aimed to quantify the effect sizes of risk factors on mortality using various machine learning approaches. A cohort of 3284 HD patients ...
Hospital Length of Stay Prediction for Planned Admissions Using Observational Medical Outcomes Partnership Common Data Model: Retrospective Study.
Journal of medical Internet research
Nov 22, 2024
BACKGROUND: Accurate hospital length of stay (LoS) prediction enables efficient resource management. Conventional LoS prediction models with limited covariates and nonstandardized data have limited reproducibility when applied to the general populati...
Bidirectional Long Short-Term Memory-Based Detection of Adverse Drug Reaction Posts Using Korean Social Networking Services Data: Deep Learning Approaches.
JMIR medical informatics
Nov 20, 2024
BACKGROUND: Social networking services (SNS) closely reflect the lives of individuals in modern society and generate large amounts of data. Previous studies have extracted drug information using relevant SNS data. In particular, it is important to de...
Improving fecal bacteria estimation using machine learning and explainable AI in four major rivers, South Korea.
The Science of the total environment
Nov 19, 2024
This study addresses the critical public health issue of fecal coliform contamination in the four major rivers in South Korea (Han, Nakdong, Geum, and Yeongsan rivers) by applying advanced machine learning (ML) algorithms combined with Explainable Ar...
Prediction model and technical and tactical decision analysis of women's badminton singles based on machine learning.
PloS one
Nov 14, 2024
In the Paris Olympic cycle, South Korean women's athlete An Se-young rose to the top of the 2023 BWF Olympic points with a win rate of 89.5%. With An Se-young as the subject, this paper aims to carry out technical and tactical analysis of women's bad...
Comprehensive Symptom Prediction in Inpatients With Acute Psychiatric Disorders Using Wearable-Based Deep Learning Models: Development and Validation Study.
Journal of medical Internet research
Nov 13, 2024
BACKGROUND: Assessing the complex and multifaceted symptoms of patients with acute psychiatric disorders proves to be significantly challenging for clinicians. Moreover, the staff in acute psychiatric wards face high work intensity and risk of burnou...
Development of a deep learning-based feature stream network for forecasting riverine harmful algal blooms from a network perspective.
Water research
Nov 5, 2024
Global increases in the occurrence of harmful algal blooms (HABs) are of major concern in water quality and resource management. A predictive model capable of quantifying the spatiotemporal associations between HABs and their influencing factors is r...
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