AIMC Topic: Biomarkers
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Machine-learning assisted discovery unveils novel interplay between gut microbiota and host metabolic disturbance in diabetic kidney disease.
Gut microbes
Mar 6, 2025
Diabetic kidney disease (DKD) is a serious healthcare dilemma. Nonetheless, the interplay between the functional capacity of gut microbiota and their host remains elusive for DKD. This study aims to elucidate the functional capability of gut microbio...
Development and Validation of an Electronic Health Record-Based, Pediatric Acute Respiratory Distress Syndrome Subphenotype Classifier Model.
Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies
Mar 6, 2025
OBJECTIVE: To determine if hyperinflammatory and hypoinflammatory pediatric acute respiratory distress syndrome (PARDS) subphenotypes defined using serum biomarkers can be determined solely from electronic health record (EHR) data using machine learn...
GDF15, EGF, and Neopterin in Assessing Progression of Pediatric Chronic Kidney Disease Using Artificial Intelligence Tools-A Pilot Study.
International journal of molecular sciences
Mar 6, 2025
Cell-mediated immunity and chronic inflammation are hallmarks of chronic kidney disease (CKD). Growth differentiation factor 15 (GDF15) is a marker of inflammation and an integrative signal in stress conditions. Epidermal growth factor (EGF) is a tub...
Circulating CCN6/WISP3 in type 2 diabetes mellitus patients and its correlation with insulin resistance and inflammation: statistical and machine learning analyses.
BMC medical informatics and decision making
Mar 6, 2025
INTRODUCTION: Cellular Communication Network Factor 6 (CCN6) is an adipokine whose production undergoes significant alterations in metabolic disorders. Given the well-established link between obesity-induced adipokine dysfunction and the development ...
Development of Machine Learning Models for Predicting Radiation Dermatitis in Breast Cancer Patients Using Clinical Risk Factors, Patient-Reported Outcomes, and Serum Cytokine Biomarkers.
Clinical breast cancer
Mar 5, 2025
BACKGROUND: Radiation dermatitis (RD) is a significant side effect of radiotherapy experienced by breast cancer patients. Severe symptoms include desquamation or ulceration of irradiated skin, which impacts quality of life and increases healthcare co...
Circadian rhythm modulation in heart rate variability as potential biomarkers for major depressive disorder: A machine learning approach.
Journal of psychiatric research
Mar 4, 2025
Major depressive disorder (MDD) is associated with reduced heart rate variability (HRV), but its link to circadian rhythm modulation (CRM) of HRV is unclear. Given that depression disrupts circadian rhythms, assessing HRV fluctuations may better capt...
miRNA-Based Diagnosis of Schizophrenia Using Machine Learning.
International journal of molecular sciences
Mar 4, 2025
Diagnostic practices for schizophrenia are unreliable due to the lack of a stable biomarker. However, machine learning holds promise in aiding in the diagnosis of schizophrenia and other neurological disorders. Dysregulated miRNAs were extracted from...
Bootstrap inference and machine learning reveal core differential plasma metabolic connectome signatures in major depressive disorder.
Journal of affective disorders
Mar 3, 2025
BACKGROUND: Major depressive disorder (MDD) involves molecular alterations and pathway dysregulation. Metabolic interconnections are crucial for normal functioning, yet current analysis focuses on individual pathways or biomarkers, overlooking intric...
Investigation and validation of genes associated with endoplasmic reticulum stress in diabetic retinopathy using various machine learning algorithms.
Experimental eye research
Mar 3, 2025
BACKGROUND: Diabetic retinopathy (DR) is a common complication of diabetes, with Endoplasmic reticulum stress (ERS) playing a key role in cellular adaptation, injury, or apoptosis, impacting disease pathology. This study aimed to identify early diagn...
Applying machine learning to high-dimensional proteomics datasets for the identification of Alzheimer's disease biomarkers.
Fluids and barriers of the CNS
Mar 3, 2025
PURPOSE: This study explores the application of machine learning to high-dimensional proteomics datasets for identifying Alzheimer's disease (AD) biomarkers. AD, a neurodegenerative disorder affecting millions worldwide, necessitates early and accura...
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