Tag: Machine Learning

Researchers in Taiwan combined Temporal Convolutional Networks, Nested LSTMs, signal decomposition, and a mutation-enhanced optimizer to cut wind power forecast ...

Researchers at Sylvester Comprehensive Cancer Center have published a framework for building AI tools that personalize evidence-based support for cancer ...

Machine learning analysis of oral rinse samples from The Maastricht Study identified the protein REG1A as a non-invasive marker of ...

Machine-learning models combining clinical data and chest CT report features can probabilistically classify lung cancer subtypes in patients presenting with ...

Researchers have introduced HGA-Net, a hypergraph-based adapter that connects related examples within each mini-batch and achieves near-perfect fine-grained recognition with ...

A new heritability-optimized scoring method called RovHer identifies the rare missense variants that explain the most genetic variation in complex ...

An exploratory study combining infrared spectroscopy with mass spectrometry metabolomics shows that fibromyalgia leaves detectable molecular traces in blood, opening ...

A systematic review of 172 studies reveals how leachate from unlined dumpsites contaminates soil and groundwater, the severe health risks ...

A study of 1,117 prospective teachers in Spain and Mexico used K-Means and Gaussian Mixture Model clustering to identify three ...

Researchers have engineered Detectrons, toehold-switch biosensors coupled to retron reverse transcription, that convert specific RNA sequences inside living cells into ...

Researchers built an explainable random survival forest model that predicts overall and cancer-specific survival in postoperative gastrointestinal stromal tumor patients, ...

A physics-informed neural network constrained by biomechanical laws achieved near-perfect recall in monitoring muscle fatigue from surface EMG signals across ...

A new review in the Journal of Materials Science maps how machine learning, from graph neural networks to large language ...

Researchers have developed MLIDSC, a self-adaptive online active learning framework that maintains high accuracy on multiclass imbalanced data streams while ...

A prospective study shows that a random forest model combining shear wave elastography, contrast-enhanced ultrasound and clinical factors can predict ...

A new Smart Partial Least Squares model shows that internal technological and managerial factors together with external economic and regulatory ...

Researchers at Anna University have developed TextSummNet, a two-stage AI system that combines extractive filtering with transformer-based abstractive generation to ...

A sweeping new review in the Journal of Materials Science shows how synchrotron light, neutron scattering, advanced microscopy, molecular simulation, ...

A systematic review of 108 studies charts how machine learning transformed bioacoustics over two decades, finding that deep learning now ...

A two-center study shows that radiomic analysis of MR cytometry parameter maps outperforms mean-value-based diffusion MRI metrics for distinguishing benign ...