AIMC Topic: Machine Learning
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Balancing ethics and statistics: machine learning facilitates highly accurate classification of mice according to their trait anxiety with reduced sample sizes.
Translational psychiatry
Aug 21, 2025
Understanding how individual differences influence vulnerability to disease and responses to pharmacological treatments represents one of the main challenges in behavioral neuroscience. Nevertheless, inter-individual variability and sex-specific patt...
Immune-related adverse events of neoadjuvant immunotherapy in patients with perioperative cancer: a machine-learning-driven, decade-long informatics investigation.
Journal for immunotherapy of cancer
Aug 21, 2025
Research on neoadjuvant immunotherapy (NAI) is increasingly focusing on immunotherapy-related adverse events (AEs). However, many unknowns remain in this field. Hence, through the machine learning (ML)-driven informatics analysis, this study aimed to...
Application of Raman spectroscopy and machine learning for determination of pro-toxicant activation in CYP2E1-expressing cells.
Analytical methods : advancing methods and applications
Aug 21, 2025
Developing a convenient, accurate, and cost-effective analytical method for the detection of Cytochrome P450 (CYP) mediated drug bioactivation remains a challenge. The present study proposes a method using Raman spectroscopy (RS) combined with machin...
Machine learning-assisted MALDI-MSI to characterize hippocampal subregion lipid and purine metabolic alterations in depression-related dry eye disease.
Analytical methods : advancing methods and applications
Aug 21, 2025
Dry eye disease (DED) and depression exhibit high comorbidity, yet lipid and purine diagnostic biomarkers for depression-related DED remain unidentified. In this study, matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI)...
High-throughput screening accelerated by machine learning for the morphology of silica nanoparticles with high cell permeability.
Nanoscale
Aug 21, 2025
In recent years, silica nanoparticles have garnered tremendous attention as drug-delivery carriers. However, the cell permeability of nanoparticles remains a major obstacle that limits the drug-delivery efficiency of drug carriers. It is a common pra...
The additive effect of the estimated glucose disposal rate and a body shape index on cardiovascular disease: A cross-sectional study.
PloS one
Aug 21, 2025
BACKGROUND: The glucose disposal rate (eGDR) and a body shape index (ABSI) are predictors strongly associated with cardiovascular disease (CVD) and outcomes. However, whether they have additive effects on CVD risk is unknown. This study aimed to inve...
A hybrid approach for forecasting peak expiratory flow rate in asthma patients using combined linear regression and random forest model.
PloS one
Aug 21, 2025
Asthma is a frequent and long-lasting disorder associated with airway inflammation. The disease severity may lead to serious health concerns and even mortality. In this work, we propose a novel hybrid approach using machine learning models and simila...
Advancing fall risk prediction in older adults with cognitive frailty: A machine learning approach using 2-year clinical data.
PloS one
Aug 21, 2025
Falls are a critical concern in older adults with cognitive frailty (CF). However, previous studies have not fully examined whether machine learning models can predict falls in older individuals with CF. The 2-year longitudinal data set from the Kore...
Medication adherence among Jordanian adults with chronic conditions: a combined analysis using regression and machine learning.
Annals of medicine
Aug 20, 2025
BACKGROUND: Managing chronic illness effectively depends not only on treatment availability but also on patients' ability to adhere to prescribed medications.
AlzFormer: Multi-modal framework for Alzheimer's classification using MRI and graph-embedded demographics guided by adaptive attention gating.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Aug 20, 2025
Alzheimer's disease (AD) is the most common neurodegenerative progressive disorder and the fifth-leading cause of death in older people. The detection of AD is a very challenging task for clinicians and radiologists due to the complex nature of this ...
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