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Biomarkers

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Utilizing integrated bioinformatics and machine learning approaches to elucidate biomarkers linking sepsis to fatty acid metabolism-associated genes.

Scientific reports
Sepsis, characterized as a systemic inflammatory response triggered by the invasion of pathogens, represents a continuum that may escalate from mild systemic infection to severe sepsis, potentially resulting in septic shock and multiple organ dysfunc...

Machine learning identifies cytokine signatures of disease severity and autoantibody profiles in systemic lupus erythematosus - a pilot study.

Scientific reports
Disrupted cytokine networks and autoantibodies play an important role in the pathogenesis of systemic lupus erythematosus. However, conflicting reports and non-reproducibility have hindered progress regarding the translational potential of cytokines ...

Machine learning-based prediction of elevated N terminal pro brain natriuretic peptide among US general population.

ESC heart failure
AIMS: Natriuretic peptide-based pre-heart failure screening has been proposed in recent guidelines. However, an effective strategy to identify screening targets from the general population, more than half of which are at risk for heart failure or pre...

Accurate non-invasive detection of MASH with fibrosis F2-F3 using a lightweight machine learning model with minimal clinical and metabolomic variables.

Metabolism: clinical and experimental
BACKGROUND: There are no known non-invasive tests (NITs) designed for accurately detecting metabolic dysfunction-associated steatohepatitis (MASH) with liver fibrosis stages F2-F3, excluding cirrhosis-the FDA-defined range for prescribing Resmetirom ...

A Transcriptomics-Based Machine Learning Model Discriminating Mild Cognitive Impairment and the Prediction of Conversion to Alzheimer's Disease.

Cells
The clinical spectrum of Alzheimer's disease (AD) ranges dynamically from asymptomatic and mild cognitive impairment (MCI) to mild, moderate, or severe AD. Although a few disease-modifying treatments, such as lecanemab and donanemab, have been develo...

A machine learning prediction model for Cardiac Amyloidosis using routine blood tests in patients with left ventricular hypertrophy.

Scientific reports
Current approaches for cardiac amyloidosis (CA) identification are time-consuming, labor-intensive, and present challenges in sensitivity and accuracy, leading to limited treatment efficacy and poor prognosis for patients. In this retrospective study...

Image biomarkers and explainable AI: handcrafted features versus deep learned features.

European radiology experimental
Feature extraction and selection from medical data are the basis of radiomics and image biomarker discovery for various architectures, including convolutional neural networks (CNNs). We herein describe the typical radiomics steps and the components o...

Towards real-time myocardial infarction diagnosis: a convergence of machine learning and ion-exchange membrane technologies leveraging miRNA signatures.

Lab on a chip
Rapid diagnosis of acute myocardial infarction (AMI) is crucial for optimal patient management. Accurate diagnosis and time of onset of an acute event can influence treatment plans, such as percutaneous coronary intervention (PCI). PCI is most benefi...

Comprehensive analysis and validation of TP73 as a biomarker for calcium oxalate nephrolithiasis using machine learning and in vivo and in vitro experiments.

Urolithiasis
Calcium oxalate (CaOx) nephrolithiasis constitutes approximately 75% of nephrolithiasis cases, resulting from the supersaturation and deposition of CaOx crystals in renal tissues. Despite their prevalence, precise biomarkers for CaOx nephrolithiasis ...

Identification and validation of biomarkers related to mitochondria during ex vivo lung perfusion for lung transplants based on machine learning algorithm.

Gene
BACKGROUND: Ex vivo lung perfusion (EVLP) is a critical strategy to rehabilitate marginal donor lungs, thereby increasing lung transplantation (LTx) rates. Ischemia-reperfusion (I/R) injury inevitably occurs during LTx. Exploring the common mechanism...