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Biomarkers

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Identification of hub biomarkers in liver post-metabolic and bariatric surgery using comprehensive machine learning (experimental studies).

International journal of surgery (London, England)
BACKGROUND: The global prevalence of non-alcoholic fatty liver disease (NAFLD) is approximately 30%, and the condition can progress to non-alcoholic steatohepatitis, cirrhosis, and hepatocellular carcinoma. Metabolic and bariatric surgery (MBS) has b...

Untargeted metabolomics and machine learning unveil the exposome and metabolism linked with the risk of early pregnancy loss.

Journal of hazardous materials
Early pregnancy loss (EPL) may result from exposure to emerging contaminants (ECs), although the underlying mechanisms remain poorly understood. This case-control study measured over 2000 serum features, including 37 ECs, 6 biochemicals, and 2057 end...

Predicting conversion in cognitively normal and mild cognitive impairment individuals with machine learning: Is the CSF status still relevant?

Alzheimer's & dementia : the journal of the Alzheimer's Association
INTRODUCTION: Machine learning (ML) helps diagnose the mild cognitive impairment-Alzheimer's disease (MCI-AD) spectrum. However, ML is fed with data unavailable in standard clinical practice. Thus, we tested a novel multi-step ML approach to predict ...

Preclinical Cognitive Markers of Alzheimer Disease and Early Diagnosis Using Virtual Reality and Artificial Intelligence: Literature Review.

JMIR medical informatics
BACKGROUND: This review explores the potential of virtual reality (VR) and artificial intelligence (AI) to identify preclinical cognitive markers of Alzheimer disease (AD). By synthesizing recent studies, it aims to advance early diagnostic methods t...

Alzheimer's disease: an integrative bioinformatics and machine learning analysis reveals glutamine metabolism-associated gene biomarkers.

BMC pharmacology & toxicology
BACKGROUND: Alzheimer's disease (AD), a hallmark of age-related cognitive decline, is defined by its unique neuropathology. Metabolic dysregulation, particularly involving glutamine (Gln) metabolism, has emerged as a critical but underexplored aspect...

Identification of biomarkers associated with coronary artery disease and non-alcoholic fatty liver disease by bioinformatics analysis and machine learning.

Scientific reports
The constantly emerging evidence indicates a close association between coronary artery disease (CAD) and non-alcoholic fatty liver disease (NAFLD). However, the exact mechanisms underlying their mutual relationship remain undefined. This study aims t...

Identification of WDR74 and TNFRSF12A as biomarkers for early osteoarthritis using machine learning and immunohistochemistry.

Frontiers in immunology
BACKGROUND: Osteoarthritis (OA) is a chronic joint condition that causes pain, limited mobility, and reduced quality of life, posing a threat to healthy aging. Early detection is crucial for improving prognosis. Recent research has focused on the rol...

An unsupervised learning approach for clustering joint trajectories of Alzheimer's disease biomarkers: An application to ADNI Data.

Alzheimer's & dementia : the journal of the Alzheimer's Association
INTRODUCTION: Current models of Alzheimer's disease (AD) progression assume a common pattern and pathology, oversimplifying the heterogeneity of clinical AD.

Identification of ubiquitination-related key biomarkers and immune infiltration in Crohn's disease by bioinformatics analysis and machine learning.

Scientific reports
Crohn's disease (CD) is a chronic inflammatory bowel disease with an unknown etiology. Ubiquitination plays a significant role in the pathogenesis of CD. This study aimed to explore the functional roles of ubiquitination-related genes in CD. Differen...