AIMC Topic: Biomarkers
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Effects of prolonged oxytetracycline supplementation on freshwater stinging catfish (): a multi-biomarker approach.
Frontiers in immunology
Dec 19, 2024
BACKGROUND: Aquaculture systems that sporadically depend on antibiotics can contribute to the development of adverse effects on the fish, microbial flora and the environment. This study sought to investigate the impacts of extended oxytetracycline su...
Evaluation of a machine learning-based metabolic marker for coronary artery disease in the UK Biobank.
Atherosclerosis
Dec 18, 2024
BACKGROUND AND AIMS: An in silico quantitative score of coronary artery disease (ISCAD), built using machine learning and clinical data from electronic health records, has been shown to result in gradations of risk of subclinical atherosclerosis, cor...
Metabolomic age (MileAge) predicts health and life span: A comparison of multiple machine learning algorithms.
Science advances
Dec 18, 2024
Biological aging clocks produce age estimates that can track with age-related health outcomes. This study aimed to benchmark machine learning algorithms, including regularized regression, kernel-based methods, and ensembles, for developing metabolomi...
Exploring the prognostic impact of triglyceride-glucose index in critically ill patients with first-ever stroke: insights from traditional methods and machine learning-based mortality prediction.
Cardiovascular diabetology
Dec 18, 2024
BACKGROUND: The incidence and mortality of first-ever strokes have risen sharply, especially in the intensive care unit (ICU). Emerging surrogate for insulin resistance, triglyceride-glucose index (TyG), has been linked to stroke prognosis. We aims t...
Triglycerides
China
Length of Stay
Blood Glucose
Time Factors
Hospital Mortality
Predictive Value of Tests
Cause of Death
Stroke
Aged
Male
Middle Aged
Risk Assessment
Intensive Care Units
Female
Reproducibility of Results
Risk Factors
Prognosis
Humans
Retrospective Studies
Machine Learning
Critical Illness
Databases, Factual
Biomarkers
Dual biomarkers CT-based deep learning model incorporating intrathoracic fat for discriminating benign and malignant pulmonary nodules in multi-center cohorts.
Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Dec 16, 2024
BACKGROUND: Recent studies in the field of lung cancer have emphasized the important role of body composition, particularly fatty tissue, as a prognostic factor. However, there is still a lack of practice in combining fatty tissue to discriminate ben...
Potential shared mechanisms in atopic dermatitis and type 2 diabetes identified via transcriptomic and machine learning approaches.
Scientific reports
Dec 16, 2024
Although atopic dermatitis (AD) and type 2 diabetes mellitus (T2DM) may appear clinically and pathophysiologically unrelated, AD is a common skin disease characterized by chronic inflammation and skin barrier dysfunction, whereas T2DM is a metabolic ...
Machine Learning and Mendelian Randomization Reveal Molecular Mechanisms and Causal Relationships of Immune-Related Biomarkers in Periodontitis.
Mediators of inflammation
Dec 16, 2024
This study aimed to investigate the molecular mechanisms of periodontitis and identify key immune-related biomarkers using machine learning and Mendelian randomization (MR). Differentially expressed gene (DEG) analysis was performed on periodontitis ...
Exploratory study of extracellular matrix biomarkers for non-invasive liver fibrosis staging: A machine learning approach with XGBoost and explainable AI.
Clinical biochemistry
Dec 13, 2024
BACKGROUND: Novel circulating markers for the non-invasive staging of chronic liver disease (CLD) are in high demand. Although underutilized, extracellular matrix (ECM) components offer significant diagnostic potential. This study evaluates ECM-relat...
Mapping Thrombosis Serum Markers by H-NMR Allied with Machine Learning Tools.
Molecules (Basel, Switzerland)
Dec 13, 2024
Machine learning and artificial intelligence tools were used to investigate the discriminatory potential of blood serum metabolites for thromboembolism and antiphospholipid syndrome (APS). H-NMR-based metabonomics data of the serum samples of patient...
Identification and verification of the optimal feature genes of ferroptosis in thyroid-associated orbitopathy.
Frontiers in immunology
Dec 13, 2024
BACKGROUND: Thyroid-associated orbitopathy (TAO) is an autoimmune inflammatory disorder of the orbital adipose tissue, primarily causing oxidative stress injury and tissue remodeling in the orbital connective tissue. Ferroptosis is a form of programm...
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