OBJECTIVES: To develop a machine learning (ML)-based predictive model to determine the key predictors of dissatisfaction after occupational injury (OI).
BACKGROUND: Patients with acute coronary syndrome (ACS) who undergo percutaneous coronary intervention (PCI) remain at high risk for major adverse cardiovascular events (MACE). Conventional risk scores may not capture dynamic or nonlinear changes in ...
This study aimed to develop a novel diagnostic tool for detecting meningioma using skull X-ray images, combining deep learning with traditional machine learning classifiers. The goal was to explore the potential of using a cost-effective and widely a...
COVID-19 has had major global impacts, highlighting the importance of robust predictive surveillance and diagnostic systems to ensure effective public health responses. Traditional surveillance methods based on passive case counting and diagnostic te...
China has been identified as a major contributor to transboundary air pollution in East Asia with a great impact on downwind countries (e.g., Japan and the Republic of Korea) through transboundary transport of air pollutants. While aggressive polluti...
BACKGROUND: As data-driven medical research advances, vast amounts of medical data are being collected, giving researchers access to important information. However, issues such as heterogeneity, complexity, and incompleteness of datasets limit their ...
Given South Korea's recent 16.6% reduction in research and development (R&D) budgets for 2023, there is an urgent need for more efficient and strategic R&D policy management. Previous studies evaluating R&D outputs have primarily relied on quantitati...
BACKGROUND: Ischemic heart disease (IHD) continues to rank among the leading global causes of mortality, consistently linked to long-term exposure to fine particulate matter (PM). Despite a declining trend in the annual average PM concentration in Se...
BACKGROUND: The advancement of digital technologies has brought transformative changes across the healthcare sector, and nursing is no exception. However, existing research has largely overlooked the ethical challenges nursing students face in real-w...
This study developed a machine learning model to predict stillbirth using retrospective data from 32,953 singleton pregnancies at multi-centers in South Korea. Variables were collected at baseline, E1 (before 13 weeks of pregnancy), and T0 (before 28...
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