AIMC Topic: Biomarkers
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Unraveling pathogenesis and potential biomarkers for autism spectrum disorder associated with HIF1A pathway based on machine learning and experiment validation.
Neurobiology of disease
Dec 8, 2024
BACKGROUND: Autism spectrum disorder (ASD) is a neurodevelopmental disorder with a high social burden and limited treatments. Hypoxic condition of the brain is considered an important pathological mechanism of ASD. HIF1A is a key participant in brain...
Comparing fully automated AI body composition biomarkers at differing virtual monoenergetic levels using dual-energy CT.
Abdominal radiology (New York)
Dec 7, 2024
PURPOSE: To investigate the behavior of artificial intelligence (AI) CT-based body composition biomarkers at different virtual monoenergetic imaging (VMI) levels using dual-energy CT (DECT).
Machine Learning Applications in Acute Coronary Syndrome: Diagnosis, Outcomes and Management.
Advances in therapy
Dec 6, 2024
Acute coronary syndrome (ACS) is a leading cause of death worldwide. Prompt and accurate diagnosis of acute myocardial infarction (AMI) or ACS is crucial for improved management and prognosis of patients. The rapid growth of machine learning (ML) res...
Heparin in sepsis: current clinical findings and possible mechanisms.
Frontiers in immunology
Dec 6, 2024
Sepsis is a clinical syndrome resulting from the interaction between coagulation, inflammation, immunity and other systems. Coagulation activation is an initial factor for sepsis to develop into multiple organ dysfunction. Therefore, anticoagulant th...
Cell-free plasma telomere length correlated with the risk of cardiovascular events using machine learning classifiers.
Scientific reports
Dec 5, 2024
This retrospective study explored the association between circulating cell-free plasma telomere length (cf-TL) and coronary artery disease (CAD) and heart failure (HF). Data from 518 participants were collected, including clinical and laboratory data...
AI-CADR: Artificial Intelligence Based Risk Stratification of Coronary Artery Disease Using Novel Non-Invasive Biomarkers.
IEEE journal of biomedical and health informatics
Dec 5, 2024
Coronary artery disease (CAD) is one of the most common causes of sudden cardiac arrest, accounting for a large percentage of global mortality. A timely diagnosis and detection may save a person's life. The research suggests a methodological framewor...
Functional Connectivity Biomarker Extraction for Schizophrenia Based on Energy Landscape Machine Learning Techniques.
Sensors (Basel, Switzerland)
Dec 4, 2024
Brain connectivity represents the functional organization of the brain, which is an important indicator for evaluating neuropsychiatric disorders and treatment effects. Schizophrenia is associated with impaired functional connectivity but characteriz...
Integrative analysis of PANoptosis-related genes in diabetic retinopathy: machine learning identification and experimental validation.
Frontiers in immunology
Dec 4, 2024
BACKGROUND: Diabetic retinopathy (DR) is a major complication of diabetes, leading to severe vision impairment. Understanding the molecular mechanisms, particularly PANoptosis, underlying DR is crucial for identifying potential biomarkers and therape...
Random Forest
Humans
Memory T Cells
CD4-Positive T-Lymphocytes
Machine Learning
Gene Regulatory Networks
Fatty Acid Synthase, Type I
Diabetic Retinopathy
Gene Expression Regulation
Biomarkers
Phospholipid Transfer Proteins
Nomograms
Molecular Targeted Therapy
ROC Curve
Regulated Cell Death
RNA-Seq
Human Umbilical Vein Endothelial Cells
RNA Editing Signatures Powered by Artificial Intelligence: A New Frontier in Differentiating Schizophrenia, Bipolar, and Schizoaffective Disorders.
International journal of molecular sciences
Dec 3, 2024
Mental health disorders are devastating illnesses, often misdiagnosed due to overlapping clinical symptoms. Among these conditions, bipolar disorder, schizophrenia, and schizoaffective disorder are particularly difficult to distinguish, as they share...
Identification of diagnostic biomarkers and molecular subtype analysis associated with m6A in Tuberculosis immunopathology using machine learning.
Scientific reports
Dec 2, 2024
Tuberculosis (TB), ranking just below COVID-19 in global mortality, is a highly complex infectious disease involving intricate immunological molecules, diverse signaling pathways, and multifaceted immune processes. N6-methyladenosine (m6A), a critica...
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