Results 201 to 210 of about 7,448,686 (319)
Objective This study aims to investigate lifestyle‐related factors in patients with psoriatic arthritis (PsA) and their association with disease activity measurements. Methods This multicenter cohort included 938 patients newly diagnosed with PsA, between 2013 and 2023. A composite lifestyle risk score (range 0 to 5) was calculated using five lifestyle‐
Batoul Hojeij +11 more
wiley +1 more source
Global maternal and infant health monitoring systems: a scoping review protocol. [PDF]
Al-Habbal K +4 more
europepmc +1 more source
This article presents the NFDI‐MatWerk Ontology (MWO), a Basic Formal Ontology‐based framework for interoperable research data management in materials science and engineering (MSE). Covering consortium structures, research data management resources, services, and instruments, MWO enables semantic integration, Findable, Accessible, Interoperable, and ...
Hossein Beygi Nasrabadi +4 more
wiley +1 more source
MEDISAN en Open Journal Systems: flujo editorial, principales dificultades y proyecciones
El incremento en la edición de revistas científicas en soporte electrónico cambió los estilos de trabajo y diseñó nuevos patrones de comunicación científica en el sector de la salud, lo que impuso a los científicos nuevas vías para compartir sus ...
Xiomara Cascaret Soto +1 more
doaj
Beyond access: reframing clinical uncertainty in trauma systems. [PDF]
Valderrama Vergara OM, Quiodettis M.
europepmc +1 more source
Evaluating Energy Absorption Performance of Filled Lattice Structures
Maximum stress must be considered to robustly evaluate energy absorber designs. This approach was applied to compare all types of absorbers in a single Ashby diagram and determine the utility of filling lattice voids with a second material. High‐performance fillers can improve the performance of lattices that are limited by buckling or catastrophic ...
Christian Bonney +2 more
wiley +1 more source
LibppRPA: An open-source library for particle-particle random phase approximation. [PDF]
Yu J, Li J, Zhang C, Zhu T, Yang W.
europepmc +1 more source
Unleashing the Power of Machine Learning in Nanomedicine Formulation Development
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore +7 more
wiley +1 more source
Open Systems Pharmacology Community Conference (OSP-CC) Proceedings 2025. [PDF]
Cordes H +35 more
europepmc +1 more source

