AIMC Topic: Biomarkers

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Deep Learning-Assisted Nanocavity Sensor for Amphiphilic Biomarker Analysis.

Analytical chemistry
Fluorescence enhancement using nanocavity structures is a promising approach for rapid detection of amphiphilic biomarkers, which are essential for diagnosing diseases such as cancer and infections. This paper presents the use of a silver nanocube (A...

Integration of Metabolomics, Lipidomics, and Machine Learning for Developing a Biomarker Panel to Distinguish the Severity of Metabolic-Associated Fatty Liver Disease.

Biomedical chromatography : BMC
Metabolic-associated fatty liver disease (MAFLD), a global health challenge linked to metabolic syndrome, requires accurate severity stratification for clinical management. Current invasive diagnostic methods limit practical implementation. This stud...

Predictive modeling of ARDS mortality integrating biomarker/cytokine, clinical and metabolomic data.

Translational research : the journal of laboratory and clinical medicine
Acute Respiratory Distress Syndrome (ARDS), characterized by the rapid onset of respiratory failure and mortality rates of ∼40%, remains a significant challenge in critical care medicine. Despite advances in supportive care, accurate prediction of AR...

Integration of metabolomics and machine learning for precise management and prevention of cardiometabolic risk in Asians.

Clinical nutrition (Edinburgh, Scotland)
Rapid changes in dietary patterns have led to a rise in cardiometabolic diseases (CMDs) worldwide, highlighting the urgent need for effective dietary strategies to address the health issues. Compared to Caucasians, Asians are more susceptible to CMDs...

A novel metabolomic aging score - better than conventional metrics in predicting short-term mortality.

Expert review of molecular diagnostics
INTRODUCTION: Accurate prediction of short-term mortality is crucial for optimizing clinical prognosis and providing treatment decisions. Conventional metrics, including physiological indicators, laboratory indexes and scoring systems, suffer from li...

Identification and analysis of diagnostic markers related to lactate metabolism in myocardial infarction.

Pathology, research and practice
Lactate metabolism is implicated in myocardial infarction (MI), yet the underlying mechanisms are not fully understood. Identifying lactate metabolism-related genes (LMRGs) could uncover new diagnostic and therapeutic targets for MI. We conducted a b...

Identifying metabolites of new psychoactive substances using in silico prediction tools.

Archives of toxicology
New psychoactive substances (NPS) pose an increasing challenge for clinical and forensic toxicology due to the initial lack of analytical and metabolic data. This study evaluates the performance of four in silico prediction tools (GLORYx, BioTransfor...

Machine learning approaches for classifying major depressive disorder using biological and neuropsychological markers: A meta-analysis.

Neuroscience and biobehavioral reviews
Traditional diagnostic methods for major depressive disorder (MDD), which rely on subjective assessments, may compromise diagnostic accuracy. In contrast, machine learning models have the potential to classify and diagnose MDD more effectively, reduc...

MACHINE LEARNING AND BIOINFORMATICS TO IDENTIFY COAGULATION BIOMARKERS IN SEPSIS-RELATED KIDNEY INJURY.

Shock (Augusta, Ga.)
Background: Sepsis-associated acute kidney injury (SA-AKI) is a life-threatening complication with mortality rates exceeding 50%, yet its molecular drivers remain poorly defined. Dysregulated coagulation is increasingly implicated in SA-AKI pathogene...

Associations of dietary patterns with serum 25(OH) vitamin D and serum anemia related biomarkers among expectant mothers: A machine learning based approach.

International journal of medical informatics
BACKGROUND: Machine learning algorithms (MLA) gained prominence in nutritional epidemiology for analyzing dietary associations and uncovering intricate patterns within data. We explored dietary patterns associated with serum iron biomarkers and vitam...