AIMC Topic: Biomarkers
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Exploring the potential of cell-free RNA and Pyramid Scene Parsing Network for early preeclampsia screening.
BMC pregnancy and childbirth
Apr 14, 2025
BACKGROUND: Circulating cell-free RNA (cfRNA) is gaining recognition as an effective biomarker for the early detection of preeclampsia (PE). However, the current methods for selecting disease-specific biomarkers are often inefficient and typically on...
c-Triadem: A constrained, explainable deep learning model to identify novel biomarkers in Alzheimer's disease.
PloS one
Apr 14, 2025
Alzheimer's disease (AD) is a neurodegenerative disorder that requires early diagnosis for effective management. However, issues with currently available diagnostic biomarkers preclude early diagnosis, necessitating the development of alternative bio...
Identification of potential markers of elevated anticandidal activity of propolis extracts.
Journal of ethnopharmacology
Apr 11, 2025
ETHNOPHARMACOLOGICAL RELEVANCE: For centuries, propolis has been one of the most important and popular antimicrobial (antibacterial and antifungal) agents used in traditional medicine worldwide, including Central and Eastern Europe. Despite centuries...
Machine learning-based integration reveals reliable biomarkers and potential mechanisms of NASH progression to fibrosis.
Scientific reports
Apr 11, 2025
Non-alcoholic fatty liver disease (NAFLD) affects about 25% of adults worldwide. Its advanced form, non-alcoholic steatohepatitis (NASH), is a major cause of liver fibrosis, but there are no non-invasive tests for diagnosing or preventing it. In our ...
Leveraging machine learning in precision medicine to unveil organochlorine pesticides as predictive biomarkers for thyroid dysfunction.
Scientific reports
Apr 11, 2025
Exposure to organochlorine pesticides (OCPs) poses significant health risks, including cancer, endocrine dysregulation, neurological disorders, and reproductive disruption. This study investigates the association between OCP exposure and thyroid dist...
Oxidative Stress Markers and Prediction of Severity With a Machine Learning Approach in Hospitalized Patients With COVID-19 and Severe Lung Disease: Observational, Retrospective, Single-Center Feasibility Study.
JMIR formative research
Apr 11, 2025
BACKGROUND: Serious pulmonary pathologies of infectious, viral, or bacterial origin are accompanied by inflammation and an increase in oxidative stress (OS). In these situations, biological measurements of OS are technically difficult to obtain, and ...
Identification of novel metabolism-related biomarkers of Kawasaki disease by integrating single-cell RNA sequencing analysis and machine learning algorithms.
Frontiers in immunology
Apr 10, 2025
BACKGROUND: The bile acid metabolism (BAM) and fatty acid metabolism (FAM) have been implicated in Kawasaki disease (KD), but their precise mechanisms remain unclear. Identifying signature cells and genes related to BAM and FAM could offer a deeper u...
Voice biomarkers as prognostic indicators for Parkinson's disease using machine learning techniques.
Scientific reports
Apr 9, 2025
Many people suffer from Parkinson's disease globally, a complicated neurological condition caused by the deficiency of dopamine, an organic chemical responsible for regulating movement in individuals. Patients with Parkinson face muscle stiffness or ...
A comparison of neural networks and regression-based approaches for estimating kidney function in pediatric chronic kidney disease: Practical predictive epidemiology for clinical management of a progressive disease.
Annals of epidemiology
Apr 8, 2025
PURPOSE: Clinical management of pediatric chronic kidney disease requires estimation of glomerular filtration rate (eGFR). Currently, eGFR is determined by two endogenous markers measured in blood: serum creatine (SCr) and cystatin C (CysC). Machine ...
Machine learning integration of multimodal data identifies key features of circulating NT-proBNP in people without cardiovascular diseases.
Scientific reports
Apr 8, 2025
N-Terminal Pro-Brain Natriuretic Peptide (NT-proBNP) is important for diagnosing and predicting heart failure or many other diseases. However, few studies have comprehensively assessed the factors correlated with NT-proBNP levels in people with cardi...
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