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Biomarkers

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Unveiling NLR pathway signatures: EP300 and CPN60 markers integrated with clinical data and machine learning for precision NASH diagnosis.

Cytokine
BACKGROUND: Given the increasing prevalence of metabolic dysfunction-associated fatty liver disease (MAFLD) and non-alcoholic steatohepatitis (NASH), there is a critical need for accurate non-invasive early diagnostic markers.

Energy-Confinement 3D Flower-Shaped Cages for AI-Driven Decoding of Metabolic Fingerprints in Cardiovascular Disease Diagnosis.

ACS nano
Rapid and accurate detection plays a critical role in improving the survival and prognosis of patients with cardiovascular disease, but traditional detection methods are far from ideal for those with suspected conditions. Metabolite analysis based on...

Machine learning-based plasma metabolomics for improved cirrhosis risk stratification.

BMC gastroenterology
BACKGROUND: Cirrhosis is a leading cause of mortality in patients with chronic liver disease (CLD). The rapid development of metabolomic technologies has enabled the capture of metabolic changes related to the progression of cirrhosis.

Deep Learning-Enhanced Chemiluminescence Vertical Flow Assay for High-Sensitivity Cardiac Troponin I Testing.

Small (Weinheim an der Bergstrasse, Germany)
Democratizing biomarker testing at the point-of-care requires innovations that match laboratory-grade sensitivity and precision in an accessible format. Here, high-sensitivity detection of cardiac troponin I (cTnI) is demonstrated through innovations...

Advancing optical nanosensors with artificial intelligence: A powerful tool to identify disease-specific biomarkers in multi-omics profiling.

Talanta
Multi-omics profiling integrates genomic, epigenomic, transcriptomic, and proteomic data, essential for understanding complex health and disease pathways. This review highlights the transformative potential of combining optical nanosensors with artif...

Interoperable Models for Identifying Critically Ill Children at Risk of Neurologic Morbidity.

JAMA network open
IMPORTANCE: Decreasing mortality in the field of pediatric critical care medicine has shifted practicing clinicians' attention to preserving patients' neurodevelopmental potential as a main objective. Earlier identification of critically ill children...

AFMDD: Analyzing Functional Connectivity Feature of Major Depressive Disorder by Graph Neural Network-Based Model.

Journal of computational biology : a journal of computational molecular cell biology
The extraction of biomarkers from functional connectivity (FC) in the brain is of great significance for the diagnosis of mental disorders. In recent years, with the development of deep learning, several methods have been proposed to assist in the di...

Artificial Intelligence in Ischemic Heart Disease Prevention.

Current cardiology reports
PURPOSE OF REVIEW: This review discusses the transformative potential of artificial intelligence (AI) in ischemic heart disease (IHD) prevention. It explores advancements of AI in predictive modeling, biomarker discovery, and cardiovascular imaging. ...