AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Biomarkers

Showing 231 to 240 of 1630 articles

Clear Filters

Interpretable machine learning-driven biomarker identification and validation for Alzheimer's disease.

Scientific reports
Alzheimer's disease (AD) is a neurodegenerative disorder characterized by limited effective treatments, underscoring the critical need for early detection and diagnosis to improve intervention outcomes. This study integrates various bioinformatics me...

Association between serum endocan levels and organ failure in hospitalized patients with cirrhosis.

PloS one
BACKGROUND & AIMS: Acute-on-chronic liver failure is a syndrome characterized by organ failure and high short-term mortality. The lack of reliable biomarkers for the early detection of acute-on-chronic liver failure is a significant challenge. Endoth...

The predictive value of heparin-binding protein for bacterial infections in patients with severe polytrauma.

PloS one
INTRODUCTION: Heparin-binding protein is an inflammatory factor with predictive value for sepsis and participates in the inflammatory response through antibacterial effects, chemotaxis, and increased vascular permeability. The role of heparin-binding...

Proteome profiling of cerebrospinal fluid using machine learning shows a unique protein signature associated with APOE4 genotype.

Aging cell
Proteome changes associated with APOE4 variant carriage that are independent of Alzheimer's disease (AD) pathology and diagnosis are unknown. This study investigated APOE4 proteome changes in people with AD, mild cognitive impairment, and no impairme...

A comprehensive and bias-free machine learning approach for risk prediction of preeclampsia with severe features in a nulliparous study cohort.

BMC pregnancy and childbirth
Preeclampsia is one of the leading causes of maternal morbidity, with consequences during and after pregnancy. Because of its diverse clinical presentation, preeclampsia is an adverse pregnancy outcome that is uniquely challenging to predict and mana...

Nonlinear relationship between serum Klotho and chronic kidney disease in US adults with metabolic syndrome.

Frontiers in endocrinology
BACKGROUND: Current evidence regarding the effects of serum Klotho among patients with metabolic syndrome (MetS) is scarce. This study explored the relationship between serum Klotho levels and the odds of chronic kidney disease (CKD) in middle-aged a...

Understanding Parkinson's: The microbiome and machine learning approach.

Maturitas
OBJECTIVE: Given that Parkinson's disease is a progressive disorder, with symptoms that worsen over time, our goal is to enhance the diagnosis of Parkinson's disease by utilizing machine learning techniques and microbiome analysis. The primary object...

Deep Learning-Enabled Rapid Metabolic Decoding of Small Extracellular Vesicles via Dual-Use Mass Spectroscopy Chip Array.

Analytical chemistry
The increasing focus of small extracellular vesicles (sEVs) in liquid biopsy has created a significant demand for streamlined improvements in sEV isolation methods, efficient collection of high-quality sEV data, and powerful rapid analysis of large d...

Identification and experimental validation of diagnostic and prognostic genes CX3CR1, PID1 and PTGDS in sepsis and ARDS using bulk and single-cell transcriptomic analysis and machine learning.

Frontiers in immunology
BACKGROUND: Sepsis is an uncontrolled reaction to infection that causes severe organ dysfunction and is a primary cause of ARDS. Patients suffering both sepsis and ARDS have a poor prognosis and high mortality. However, the mechanisms behind their si...