An attention‐based multimodal deep learning framework is developed to predict the creep life of Ni‐based superalloys by fusing processing parameters with microstructural micrographs. The model achieves high accuracy (R2 = 0.92), aligns with metallurgical principles by capturing δ‐phase influence, and incorporates uncertainty quantification, offering a ...
Haopeng Lv +10 more
wiley +1 more source
Does Lower Regression Error Mean Stronger Forensic Evidence? Machine Learning Regression Versus Demirjian and Willems Methods for Dental Age Estimation at 12- and 15-Year Legal Thresholds. [PDF]
Doğan M +5 more
europepmc +1 more source
ProMetNet introduces a biologically constrained deep learning framework for proteo‐metabolomic integration by embedding Reactome‐derived pathway topology into neural networks. It captures non‐linear molecular dependencies and pathway‐level metabolic reorganization, enabling interpretable discrimination.
Minghui Zhao +6 more
wiley +1 more source
Effects of Forest Therapy on Depressive Symptoms: A Systematic Review and Meta-Analysis. [PDF]
Lu K, Tang A, Liu Y, Cao F.
europepmc +1 more source
Application of the Random Forest Method for Classifying Diabetes
Eka Putri Yuniarsih +3 more
openaire +1 more source
Learning from pandemics: Feature selection and clustering for robust digital disease nowcasting. [PDF]
Mesquita S +4 more
europepmc +1 more source
A Hybrid Random Forest-SARSA Framework for Resting-State EEG-Based Parkinson's Disease Detection With Temporal Decision Refinement. [PDF]
S S, Rajan SE.
europepmc +1 more source
Neurophysiological Characterization of ADHD in Children Using EEG Signals: A Machine Learning Approach to Executive Function Networks. [PDF]
Gutiérrez-Jácome DB +3 more
europepmc +1 more source
A configurable five-step workflow for high-throughput hyperspectral image analysis and vegetation index mapping. [PDF]
Jung JG +4 more
europepmc +1 more source

