AIMC Topic: Machine Learning
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Gastrointestinal bleeding detection on digital subtraction angiography using convolutional neural networks with and without temporal information.
Diagnostic and interventional radiology (Ankara, Turkey)
Aug 7, 2025
PURPOSE: Digital subtraction angiography (DSA) offers a real-time approach to locating lower gastrointestinal (GI) bleeding. However, many sources of bleeding are not easily visible on angiograms. This investigation aims to develop a machine learning...
Childhood trauma and adolescent anxiety: Uncovering emotion regulation pathways through integrated machine learning and traditional statistics.
Psychiatry research
Aug 7, 2025
Childhood trauma constitutes a significant risk factor for adolescent anxiety, with emotion regulation playing a critical role. This large-scale longitudinal study (N = 2461 at baseline, with external validation) examined differential relationships b...
ConfRank+: Extending Conformer Ranking to Charged Molecules.
Journal of chemical information and modeling
Aug 7, 2025
We present a machine learning model for high-throughput energetic ranking of charged molecular conformers. Based on the ConfRank (Hölzer et al. , 8909-8925) approach, the model is trained in a pairwise fashion to predict energy differences for pair...
Finerenone Modulates PANoptosis to Improve Immune Microenvironment in Diabetic Nephropathy: A Machine Learning-Based Mechanistic Analysis.
Journal of molecular neuroscience : MN
Aug 7, 2025
Diabetic nephropathy (DN) is characterized by nephron degeneration induced by hyperglycemia, driven by complex interactions between glucose metabolism dysregulation and immune microenvironment dynamics. This study employed machine learning and bioinf...
Machine learning-based proteomics profiling of ALS identifies downregulation of RPS29 that maintains protein homeostasis and STMN2 level.
Communications biology
Aug 7, 2025
Amyotrophic lateral sclerosis (ALS) is a devastating motor neuron disease. The molecular understanding of ALS is hampered by the lack of experimental models recapitulating disease heterogeneity and analytical framework integrating multi-omics dataset...
Machine learning based classification of catastrophic health expenditures: a cross-sectional study of Korean low-income households.
BMC health services research
Aug 7, 2025
BACKGROUND: Despite the National Health Insurance (NHI) system implemented in South Korea, concerns persist regarding access to health coverage for low-income households. To address this issue, this study aims to use machine learning-based data minin...
Explainable illicit drug abuse prediction using hematological differences.
Scientific reports
Aug 7, 2025
This study aimed to develop a reliable and explainable predictive model for illicit drug use (IDU). The model uses a machine learning (ML) algorithm to predict IDU using hematological differences between illicit drug users (IDUr) and non-users (n-IDU...
Machine learning derived development and validation of extracellular matrix related signature for predicting prognosis in adolescents and young adults glioma.
Scientific reports
Aug 7, 2025
The mortality rates have been increasing for glioma in adolescents and young adults (AYAs, aged 15-39 years). However, current biomarkers for clinical assessment in AYAs glioma are limited, prompting the urgent need for identifying ideal prognostic s...
Development of several machine learning based models for determination of small molecule pharmaceutical solubility in binary solvents at different temperatures.
Scientific reports
Aug 7, 2025
Analysis of small-molecule drug solubility in binary solvents at different temperatures was carried out via several machine learning models and integration of models to optimize. We investigated the solubility of rivaroxaban in both dichloromethane a...
Developing an Equitable Machine Learning-Based Music Intervention for Older Adults At Risk for Alzheimer Disease: Protocol for Algorithm Development and Validation.
JMIR research protocols
Aug 7, 2025
BACKGROUND: Given the high prevalence and cost of Alzheimer disease (AD), it is crucial to develop equitable interventions to address lifestyle factors associated with AD incidence (eg, depression). While lifestyle interventions show promise for redu...
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