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Biomarkers

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Subtyping strokes using blood-based protein biomarkers: A high-throughput proteomics and machine learning approach.

European journal of clinical investigation
BACKGROUND: Rapid diagnosis of stroke and its subtypes is critical in early stages. We aimed to discover and validate blood-based protein biomarkers to differentiate ischemic stroke (IS) from intracerebral haemorrhage (ICH) using high-throughput prot...

MRI classification of progressive supranuclear palsy, Parkinson disease and controls using deep learning and machine learning algorithms for the identification of regions and tracts of interest as potential biomarkers.

Computers in biology and medicine
BACKGROUND: Quantitative magnetic resonance imaging (MRI) analysis has shown promise in differentiating neurodegenerative Parkinsonian syndromes and has significantly advanced our understanding of diseases like progressive supranuclear palsy (PSP) in...

An exploration into the diagnostic capabilities of microRNAs for myocardial infarction using machine learning.

Biology direct
BACKGROUND: MicroRNAs (miRNAs) have shown potential as diagnostic biomarkers for myocardial infarction (MI) due to their early dysregulation and stability in circulation after MI. Moreover, they play a crucial role in regulating adaptive and maladapt...

Psoriatic arthritis in psoriasis: optimizing the current screening system for psoriatic arthritis based on serum data from U.S. and Chinese populations.

Frontiers in immunology
BACKGROUND: Psoriatic arthritis (PSA) is an inflammatory joint disease associated with psoriasis (PSO) that can be easily missed. Existing PSA screening tools ignore objective serologic indicators. The aim of this study was to develop a disease scree...

Unraveling pathogenesis and potential biomarkers for autism spectrum disorder associated with HIF1A pathway based on machine learning and experiment validation.

Neurobiology of disease
BACKGROUND: Autism spectrum disorder (ASD) is a neurodevelopmental disorder with a high social burden and limited treatments. Hypoxic condition of the brain is considered an important pathological mechanism of ASD. HIF1A is a key participant in brain...

Machine Learning Applications in Acute Coronary Syndrome: Diagnosis, Outcomes and Management.

Advances in therapy
Acute coronary syndrome (ACS) is a leading cause of death worldwide. Prompt and accurate diagnosis of acute myocardial infarction (AMI) or ACS is crucial for improved management and prognosis of patients. The rapid growth of machine learning (ML) res...

Heparin in sepsis: current clinical findings and possible mechanisms.

Frontiers in immunology
Sepsis is a clinical syndrome resulting from the interaction between coagulation, inflammation, immunity and other systems. Coagulation activation is an initial factor for sepsis to develop into multiple organ dysfunction. Therefore, anticoagulant th...

Cell-free plasma telomere length correlated with the risk of cardiovascular events using machine learning classifiers.

Scientific reports
This retrospective study explored the association between circulating cell-free plasma telomere length (cf-TL) and coronary artery disease (CAD) and heart failure (HF). Data from 518 participants were collected, including clinical and laboratory data...

AI-CADR: Artificial Intelligence Based Risk Stratification of Coronary Artery Disease Using Novel Non-Invasive Biomarkers.

IEEE journal of biomedical and health informatics
Coronary artery disease (CAD) is one of the most common causes of sudden cardiac arrest, accounting for a large percentage of global mortality. A timely diagnosis and detection may save a person's life. The research suggests a methodological framewor...