Building machine‐readable vocabularies for materials science is slow, expert‐driven work. This study benchmarks 13 large language models on two of its first steps: finding candidate terms in engineering articles and deciding where they belong in a class hierarchy.
Thomas Bjarsch +3 more
wiley +1 more source
Code-Free AutoML for Binary Classification of Fractured and Non-fractured Bone Radiographs From a Heterogeneous Public Dataset Using Google Cloud Vertex AI: A Proof-of-Concept Study. [PDF]
Bachir MA +5 more
europepmc +1 more source
We develop a data‐driven method to derive the mathematical expressions of the Flory–Huggins interaction parameter χ for the swelling behavior of temperature–responsive hydrogels. Starting from initial assumptions of χ, our workflow combines Bayesian optimization, Flory–Rehner theory, and symbolic regression to generate candidate χ expressions.
Yawen Wang +2 more
wiley +1 more source
Machine Learning-Based Predictive Model for Functional Independence in Spinal Cord Injury: Protocol for a Predictive Rule Development and Validation Study. [PDF]
Perez-Sanpablo AI +9 more
europepmc +1 more source
The PRIMA Thesaurus for Materials Science and Engineering
The PRIMA Thesaurus is a structured vocabulary designed to improve how materials science data is described and shared. Developed with input from multiple experts, it enables clear documentation of research workflows, data exchange, and reuse across platforms.
Rossella Aversa +8 more
wiley +1 more source
A novel causality-based method for identifying drivers of breast cancer progression. [PDF]
Shen L +9 more
europepmc +1 more source
A Lightweight Procedural Layer for Hybrid Experimental–Computational Workflows in Materials Science
We unveil a prototype hybrid‐workflow framework that fuses automatedcomputation with hands‐on experiments. Built atop pyiron, a lightweight, parameterized layer translates procedure descriptions into executable manual steps, syncing instrument settings, human interventions, and data capture in real‐time today.
Steffen Brinckmann +8 more
wiley +1 more source
Explainable machine learning for predicting activities of daily living at discharge in stroke patients: A retrospective study using SHAP interpretability. [PDF]
Ye Q, Fang G, Li L, Li Q, Yang Y, Liu L.
europepmc +1 more source
PASTA‐ELN: Simplifying Research Data Management for Experimental Materials Science
Research data management faces ongoing hurdles as many ELNs remain complex and restrictive. PASTA‐ELN offers an open‐source, cross‐platform solution that prioritizes simplicity, offline access, and user control. Its in tuitive folder structure, modular Python add‐ons, and open formats enable seamless documentation, FAIR data practices, and easy ...
S. Brinckmann, G. Winkens, R. Schwaiger
wiley +1 more source
Improving Health Care Services for Autistic Young Adults: Development and Use of a Self-Reported Health Care Transition Readiness Assessment. [PDF]
Cheak-Zamora NC, Boccardi L, Bertucci G.
europepmc +1 more source

