Automated arrhythmia detection from electrocardiogram (ECG) signals is crucial and important for the early treatment of cardiac disease (CD). In this investigation, eight machine-learning models have been developed to identify improved ECG arrhythmia...
Journal of chemical information and modeling
Dec 14, 2025
Predicting essential oil yield in supercritical CO (SC-CO) extraction remains difficult due to variations in plant composition and process conditions. Conventional models often assume uniform feedstock behavior, which limits their applicability acros...
Journal of chemical information and modeling
Dec 13, 2025
Molecular dynamics (MD) simulations are powerful tools for studying biomolecular systems, but they are fundamentally limited by accessible time scales, making the study of rare events such as protein folding or ligand unbinding computationally challe...
Journal of chemical information and modeling
Dec 12, 2025
Metal-organic frameworks (MOFs) are a novel class of porous materials characterized by high surface area, high porosity, and tunable structure, possessing immense application potential. Many synthesis methods have been developed for MOFs, such as che...
BACKGROUND: Pre-mRNA alternative splicing contributes to oncogenic gene expression in hepatocellular carcinoma (HCC), and some oncogenic isoforms escape the tumor into circulation. This study aimed to characterize the alternative splicing landscape o...
Array-based biosensors hold substantial promise for rapid bacterial identification. However, conventional approaches face two key limitations: their reliance on nonspecific interactions with bacterial surfaces hinders biochemical interpretation, and ...
BACKGROUND: Acute respiratory distress syndrome (ARDS) is a common complication after type A aortic dissection surgery and often leads to worsened clinical outcomes for patients. The early prediction of postoperative ARDS is a crucial challenge in cl...
BACKGROUND: Artificial intelligence is emerging as a transformative force in pharmaceutical sciences by enabling data-driven decision-making, automation, and predictive modeling. In ocular drug delivery, where therapeutic efficacy is hindered by comp...
BACKGROUND: Opioid overuse is a costly and significant problem in the United States. Medical specialties including surgery are a contributor to opioid prescriptions while having few clear prescribing guidelines. Machine learning predictive tools can ...
Big biological datasets, such as gene expression profiles, often contain redundant features that degrade model performance and limit generalization across independent datasets with complexities like class imbalance and hidden sub-clusters. To overcom...
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