BACKGROUND: Although strategies for COVID-19 have shifted towards normalized measures globally, establishing predictive models based on Internet search data remains crucial for swiftly controlling and preventing future outbreaks. This study aims to u...
Machine learning models are powerful tools for cardiovascular disease (CVD) prediction, but their performance is often limited by dataset size and class imbalance. While data augmentation techniques can address these issues, their impact on model int...
BACKGROUND: In recent years, the incidence of ST-segment elevation myocardial infarction (STEMI) has been on the rise, leading to an increase in the number of patients undergoing direct percutaneous coronary intervention (pPCI). However, some patient...
BACKGROUND: Spontaneous preterm birth (sPTB) remains a major cause of neonatal morbidity and early risk assessment was poor. This study aimed to evaluate the association and predictive potential of serum biomarkers and maternal factors with sPTB.
Environmental pollution (Barking, Essex : 1987)
Oct 30, 2025
Despite growing global initiatives on sustainable plastic management, less than 10 % of plastic waste is effectively recycled, resulting in widespread environmental dispersion and pollution. This study examines the relative influence of topographic, ...
XGBoost, a gradient boosting algorithm, is widely recognized for its efficiency and robustness in multiclass classification tasks. Metabolomics serves as a powerful tool for biomarker discovery; however, metabolic biomarkers associated with the progr...
Air pollution is a global problem that threatens environmental sustainability and severely affects public health. Monitoring air quality and predicting future pollution levels are critical for creating effective environmental policies and enabling in...
Understanding attachment styles is essential in psychology and neuroscience, yet predicting them using objective neural data remains challenging. This study explores the use of machine learning (ML) models and EEG analysis to improve attachment style...
Coseismic landslides are among the most perilous geological disasters in hilly places after earthquakes. Precise assessment of coseismic landslide susceptibility is crucial for forecasting the effects of landslides and alleviating subsequent tragedie...
Traditional diagnostic methods for asthma, a widespread chronic respiratory illness, are often limited by factors such as patient cooperation with spirometry. Non-invasive acoustic analysis using machine learning offers a promising alternative for ob...
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