A critical narrative review synthesizes evidence from over eighty studies demonstrating that artificial intelligence applied to multiparametric magnetic resonance imaging ...
A new EEG framework improves cross-subject driving fatigue detection by using early personal spectral references and causal long-sequence residual encoding.
A causal forest model reveals that high flow nasal oxygen reduces invasive mechanical ventilation in specific subgroups of immunocompromised patients ...
Researchers developed and deployed a fine-grained natural language processing framework that accurately extracts context-aware medication details from unstructured Hungarian clinical ...
An empirical analysis of European social good initiatives reveals that while machine learning dominates classification tasks, foundational statistical methods remain ...
A review in Discover Materials explores how machine learning accelerates the design of biodegradable materials for soft robotics by bridging ...
Researchers have developed a dual-pathway computational framework that combines molecular graphs, biological knowledge networks, and semantic descriptions to predict rare ...
A multicentre derivation and validation study paired with a prospective randomised trial shows an explainable artificial intelligence ensemble predicts multiple ...
A new review argues that most ICU biomarkers still guide treatment rather than select it, and that no true companion ...
A new review maps how cellulose, lignin and other wood precursors can be turned into porous carbons, aerogels and membranes ...
A cross-tissue machine learning framework utilizing Gene Ontology pathway-level DNA methylation scores accurately identified asthma status across multiple airway epithelial ...
A peer-reviewed literature review synthesizes how the brain perceives emotion, forms emotional memories, and enables affective computing through neural decoding.
A joint deep learning framework called J-SUP unifies aspect-based sentiment analysis and consumer preference profiling within a shared Transformer architecture ...
Machine learning-driven rescoring with MS²Rescore improves peptide identification rates and taxonomic specificity in metaproteomics datasets, particularly in complex environments such ...
An Adaptive Fuzzy–Cost Benefit Analysis framework integrating fuzzy inference and adaptive threshold optimization improved EEG cognitive state classification, enabling an ...
A multiregional neural sensing framework using machine learning predicted Parkinson's disease motor fluctuations with nearly ninety percent accuracy across animal ...
Computer scientists have developed an intelligent undersampling framework that combines density-aware boundary selection with weighted ensemble learning to significantly improve ...
Researchers developed an interpretable XGBoost-SHAP framework to prioritize noncoding variants and identify nonlinear regulatory interactions affecting HNF4A binding in pancreatic ...
Researchers combining Sentinel-2A satellite imagery, InVEST ecological modeling, and machine learning determined that mangrove forests store over 10.2 million tonnes ...
Machine learning models trained on light-off data identified Co-CO3 as the most energy-efficient cobalt catalyst for toluene oxidation and the ...
