AIMC Topic: Case-Control Studies
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Graph convolutional network with attention mechanism improve major depressive depression diagnosis based on plasma biomarkers and neuroimaging data.
Journal of affective disorders
May 31, 2024
BACKGROUND: The absence of clinically-validated biomarkers or objective protocols hinders effective major depressive disorder (MDD) diagnosis. Compared to healthy control (HC), MDD exhibits anomalies in plasma protein levels and neuroimaging presenta...
Machine Learning Identifies Key Proteins in Primary Sclerosing Cholangitis Progression and Links High CCL24 to Cirrhosis.
International journal of molecular sciences
May 30, 2024
Primary sclerosing cholangitis (PSC) is a rare, progressive disease, characterized by inflammation and fibrosis of the bile ducts, lacking reliable prognostic biomarkers for disease activity. Machine learning applied to broad proteomic profiling of s...
Predicting Non-Alcoholic Steatohepatitis: A Lipidomics-Driven Machine Learning Approach.
International journal of molecular sciences
May 29, 2024
Nonalcoholic fatty liver disease (NAFLD), nowadays the most prevalent chronic liver disease in Western countries, is characterized by a variable phenotype ranging from steatosis to nonalcoholic steatohepatitis (NASH). Intracellular lipid accumulation...
An ensemble-based machine learning model for predicting type 2 diabetes and its effect on bone health.
BMC medical informatics and decision making
May 29, 2024
BACKGROUND: Diabetes is a chronic condition that can result in many long-term physiological, metabolic, and neurological complications. Therefore, early detection of diabetes would help to determine a proper diagnosis and treatment plan.
A machine-learning approach for differentiating borderline personality disorder from community participants with brain-wide functional connectivity.
Journal of affective disorders
May 26, 2024
BACKGROUND: Functional connectivity has garnered interest as a potential biomarker of psychiatric disorders including borderline personality disorder (BPD). However, small sample sizes and lack of within-study replications have led to divergent findi...
Neuroimaging Insights: Structural Changes and Classification in Ménière's Disease.
Ear and hearing
May 24, 2024
OBJECTIVES: This study aimed to comprehensively investigate the neuroanatomical alterations associated with idiopathic Ménière's disease (MD) using voxel-based morphometry and surface-based morphometry techniques. The primary objective was to explore...
Exploring T-cell exhaustion features in Acute myocardial infarction for a Novel Diagnostic model and new therapeutic targets by bio-informatics and machine learning.
BMC cardiovascular disorders
May 24, 2024
BACKGROUND: T-cell exhaustion (TEX), a condition characterized by impaired T-cell function, has been implicated in numerous pathological conditions, but its role in acute myocardial Infarction (AMI) remains largely unexplored. This research aims to i...
MicroRNA classification and discovery for major depressive disorder diagnosis: Towards a robust and interpretable machine learning approach.
Journal of affective disorders
May 22, 2024
BACKGROUND: Major depressive disorder (MDD) is notably underdiagnosed and undertreated due to its complex nature and subjective diagnostic methods. Biomarker identification would help provide a clearer understanding of MDD aetiology. Although machine...
Evaluation of choroid vascular layer thickness in wet age-related macular degeneration using artificial intelligence.
Photodiagnosis and photodynamic therapy
May 21, 2024
PURPOSE: To facilitate the assessment of choroid vascular layer thickness in patients with wet age-related macular degeneration (AMD) using artificial intelligence (AI).
A confounder controlled machine learning approach: Group analysis and classification of schizophrenia and Alzheimer's disease using resting-state functional network connectivity.
PloS one
May 20, 2024
Resting-state functional magnetic resonance imaging (rs-fMRI) has increasingly been used to study both Alzheimer's disease (AD) and schizophrenia (SZ). While most rs-fMRI studies being conducted in AD and SZ compare patients to healthy controls, it i...
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