AIMC Topic: Machine Learning

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Identification and verification of immune and oxidative stress-related diagnostic indicators for malignant lung nodules through WGCNA and machine learning.

Scientific reports Jul 1, 2025
Early detection of lung nodules (LNs) is critical for prevention and treatment of lung cancer. However, current noninvasive diagnostic methods face significant challenges in reliably distinguishing benign from malignant nodules. Thus, there is an urg...
Gene Regulatory Networks Lung Neoplasms Gene Expression Profiling Gene Expression Regulation, Neoplastic Oxidative Stress Databases, Genetic Protein Interaction Maps Humans Machine Learning Biomarkers, Tumor
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Comparative analysis of machine learning approaches for heatwave event prediction in India.

Scientific reports Jul 1, 2025
Heatwaves, are identified as prolonged durations of unusually high temperatures, which pose significant threats to human health, animal health and agriculture. With the increasing frequency and intensity of heatwaves driven by climate change, accurat...
Climate Change Humans Machine Learning Neural Networks, Computer Extreme Heat India Support Vector Machine
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Ensemble learning for biomedical signal classification: a high-accuracy framework using spectrograms from percussion and palpation.

Scientific reports Jul 1, 2025
Accurate classification of biomedical signals is crucial for advancing non-invasive diagnostic methods, particularly for identifying gastrointestinal and related medical conditions where conventional techniques often fall short. An ensemble learning ...
Ensemble Learning Palpation Humans Percussion Support Vector Machine Neural Networks, Computer Signal Processing, Computer-Assisted Machine Learning Fourier Analysis Algorithms
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Machine learning model for predicting Amyloid-β positivity and cognitive status using early-phase F-Florbetaben PET and clinical features.

Scientific reports Jul 1, 2025
This study developed machine learning models to predict Aβ positivity in Alzheimer's disease by integrating early-phase F-Florbetaben PET and clinical data to improve diagnostic accuracy. Furthermore, the study explored machine learning models to pre...
Female Aged Aged, 80 and over Male Middle Aged Humans Aniline Compounds Machine Learning Positron-Emission Tomography Cognition Cognitive Dysfunction Brain Stilbenes Amyloid beta-Peptides Alzheimer Disease
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Personalized prediction model generated with machine learning for kidney function one year after living kidney donation.

Scientific reports Jul 1, 2025
Living kidney donors typically experience approximately a 30% reduction in kidney function after donation, although the degree of reduction varies among individuals. This study aimed to develop a machine learning (ML) model to predict serum creatinin...
Nephrectomy Kidney Function Tests Living Donors Creatinine Middle Aged Kidney Glomerular Filtration Rate Humans Machine Learning Kidney Transplantation Female Adult Male
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Integrative machine learning and molecular simulation approaches identify GSK3β inhibitors for neurodegenerative disease therapy.

Scientific reports Jul 1, 2025
Neurodegenerative diseases (NDDs), including Alzheimer's disease (AD) and Parkinson's disease (PD), are a growing global health concern, especially among the elderly, posing significant challenges to well-being and survival. GSK3β, a serine/threonine...
Protein Kinase Inhibitors Glycogen Synthase Kinase 3 beta Humans Machine Learning Molecular Docking Simulation Neurodegenerative Diseases Molecular Dynamics Simulation
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Uncovering memorization effect in the presence of spurious correlations.

Nature communications Jul 1, 2025
Machine learning models often rely on simple spurious features - patterns in training data that correlate with targets but are not causally related to them, like image backgrounds in foreground classification. This reliance typically leads to imbalan...
Neural Networks, Computer Machine Learning Neurons Humans Memory
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Dissecting crosstalk induced by cell-cell communication using single-cell transcriptomic data.

Nature communications Jul 1, 2025
During cell-cell communication (CCC), pathways activated by different ligand-receptor pairs may have crosstalk with each other. While multiple methods have been developed to infer CCC networks and their downstream response using single-cell RNA-seq d...
Gene Expression Profiling Transcriptome Single-Cell Analysis Humans Machine Learning Transcription Factors Cell Communication RNA-Seq Gene Regulatory Networks Signal Transduction
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A supervised machine learning approach with feature selection for sex-specific biomarker prediction.

NPJ systems biology and applications Jul 1, 2025
Biomarkers are crucial in aiding in disease diagnosis, prognosis, and treatment selection. Machine learning (ML) has emerged as an effective tool for identifying novel biomarkers and enhancing predictive modelling. However, sex-based bias in ML algor...
Uric Acid Supervised Machine Learning Sex Factors Blood Glucose Body Mass Index Blood Pressure Machine Learning Algorithms Waist Circumference Biomarkers Female Male Middle Aged Humans
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ToxACoL: an endpoint-aware and task-focused compound representation learning paradigm for acute toxicity assessment.

Nature communications Jul 1, 2025
Multi-species acute toxicity assessment forms the basis for chemical classification, labelling and risk management. Existing deep learning methods struggle with diverse experimental conditions, imbalanced data, and scarce target data, hindering their...
Animals Deep Learning Toxicity Tests, Acute Humans Machine Learning
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