Evaluation of Molecular Phylogenetic Trees by an Information-Theoretic Metric. [PDF]
Nishimaki T, Sato K.
europepmc +1 more source
An Integrated NLP‐ML Framework for Property Prediction and Design of Steels
This study presents a data‐driven framework that uses language‐processing techniques to interpret steel processing descriptions and machine‐learning models to predict mechanical properties. By organising complex process histories into meaningful groups and enabling rapid property forecasts, the work supports faster, more informed steel design through ...
Kiran Devraju +5 more
wiley +1 more source
Machine learning versus traditional regression models for predicting diabetic retinopathy screening adherence among community-dwelling older adults with diabetes. [PDF]
Wang Y +5 more
europepmc +1 more source
Physics‐Embedded Neural Network: A Novel Approach to Design Polymeric Materials
Traditional black‐box models for polymer mechanics rely solely on data and lack physical interpretability. This work presents a physics‐embedded neural network (PENN) that integrates constitutive equations into machine learning. The approach ensures reliable stress predictions, provides interpretable parameters, and enables performance‐driven, inverse ...
Siqi Zhan +8 more
wiley +1 more source
Should we build single-cell lineage trees from gene expression data? [PDF]
Mulberry N, Stadler T.
europepmc +1 more source
Specific Random Trees for Random Forest
LIU, Zhi, SUN, Zhaocai, WANG, Hongjun
openaire +3 more sources
A regenerative strategy for stroke combines human stem cell–derived neural progenitor cells with sustained release of a matrix‐modifying, thermostable chondroitinase ABC‐37 enzyme. In a rat model of stroke, co‐delivery enhanced transplanted cell survival and neuronal differentiation, degraded inhibitory extracellular matrix components, and improved ...
Nitzan Letko Khait +7 more
wiley +1 more source
Integrating Multivariate Ordination and Machine Learning to Disentangle the Environmental Drivers of Xylem Sap Redox Metabolism in Trees. [PDF]
Kurt R, Özan ZE.
europepmc +1 more source
ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray +3 more
wiley +1 more source
Socioeconomic determinants of malaria in Ugandan children: An interpretable machine learning approach for public health policy. [PDF]
Oliveira CG +4 more
europepmc +1 more source

