AIMC Topic: Machine Learning
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Establishing identifiable characteristic fingerprints of mulberry leaves: Integrating chemical composition and bioactivity through machine learning.
Journal of ethnopharmacology
Jun 23, 2025
ETHNOPHARMACOLOGICAL RELEVANCE: Mulberry leaves (Morus alba L.) are used in traditional Chinese medicine to clear the lungs and dispel wind-heat. Despite their common use, chemical reference substance rely solely on rutin, which may not reflect their...
CellMemory: hierarchical interpretation of out-of-distribution cells using bottlenecked transformer.
Genome biology
Jun 23, 2025
Machine learning methods, especially Transformer architectures, have been widely employed in single-cell omics studies. However, interpretability and accurate representation of out-of-distribution (OOD) cells remains challenging. Inspired by the glob...
Harnessing the machine learning and nomogram models: elevating prognostication in nonmetastatic gastric cancer with "double invasion" for personalized patient care.
European journal of medical research
Jun 23, 2025
OBJECTIVE: To develop and validate a machine learning framework combined with a nomogram for predicting recurrence after radical gastrectomy in patients with vascular and neural invasion.
Classification of primary glomerulonephritis using machine learning models: a focus on IgA nephropathy prediction.
BMC nephrology
Jun 23, 2025
OBJECTIVE: IgA nephropathy (IgAN) is the most common form of glomerulonephritis worldwide, characterized by immune complex deposition in the glomerular mesangium, leading to mesangial hypercellularity, persistent microhematuria, proteinuria, and prog...
Inflammation-related 5-hydroxymethylation signatures as markers for clinical presentations of coronary artery disease.
Cardiovascular diabetology
Jun 23, 2025
BACKGROUND: Coronary angiography remains the gold standard for diagnosing coronary artery disease (CAD), but its invasive nature limits its applicability for widespread screening. Identifying non-invasive molecular markers could improve CAD classific...
Middle Aged
Risk Assessment
Severity of Illness Index
Epigenesis, Genetic
Inflammation
DNA Methylation
Cell-Free Nucleic Acids
Female
Reproducibility of Results
Aged
Male
Humans
Machine Learning
Biomarkers
Prognosis
Coronary Artery Disease
Non-ST Elevated Myocardial Infarction
Inflammation Mediators
Predictive Value of Tests
5-Methylcytosine
ST Elevation Myocardial Infarction
Exploring Factors Related to Social Isolation Among Older Adults in the Predementia Stage Using Ecological Momentary Assessments and Actigraphy: Machine Learning Approach.
Journal of medical Internet research
Jun 23, 2025
BACKGROUND: As the global population ages, the economic burden of dementia continues to rise. Social isolation-which includes limited social interaction and feelings of loneliness-negatively affects cognitive function and is a significant risk factor...
Detection of pre-ictal epileptic events using a self-attention based neural network from raw Neonatal EEG data.
Computers in biology and medicine
Jun 22, 2025
Epileptic seizures can occur unpredictably, making real-time monitoring and early warning systems critical, especially in neonatal patients, where timely intervention can significantly improve outcomes. Neonatal seizures are often subtle and difficul...
SmartAlert: Machine learning-based patient-ventilator asynchrony detection system in intensive care units.
Computer methods and programs in biomedicine
Jun 21, 2025
BACKGROUND AND OBJECTIVE: Patient-ventilator asynchronies (PVA) are associated with ventilator-induced lung injury and increased mortality. Current detection methods rely on static thresholds, extensive preprocessing, or proprietary ventilator data. ...
Cross-jurisdictional factors linked to gambling frequency in adolescents from 28 European countries: a machine learning approach.
Psychiatry research
Jun 21, 2025
Adolescents are vulnerable to experiencing problematic gambling, although its prevalence and potential risk factors vary across countries. This study aims to identify cross-jurisdictional factors associated with higher gambling frequency among adoles...
Predictive modeling of postoperative hyponatremia after pituitary adenoma surgery.
Clinical neurology and neurosurgery
Jun 21, 2025
OBJECTIVE: To improve the prediction of postoperative hyponatremia after pituitary surgery by comparing six machine learning (ML) models.
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