Getting It Out There: Reflections on the Process and Impact of Public Engagement Activities in a Study on End-of-Life Care Planning With People With Intellectual Disabilities. [PDF]
Bruun A +14 more
europepmc +1 more source
LLM‐Based Scientific Assistants for Knowledge Extraction: Which Design Choices Matter?
A comprehensive framework for optimizing Large Language Models in domain‐specific applications is introduced. The LLM Playground integrates Prompt Engineering, knowledge augmentation, and advanced reasoning strategies to enable systematic comparison of architectures and base models.
David Exler +7 more
wiley +1 more source
Automating thematic review of prevention of future deaths reports: concordance study of a child-suicide analysis using large language models. [PDF]
Osian S +4 more
europepmc +1 more source
Predictive models successfully screen nanoparticles for toxicity and cellular uptake. Yet, complex biological dynamics and sparse, nonstandardized data limit their accuracy. The field urgently needs integrated artificial intelligence/machine learning, systems biology, and open‐access data protocols to bridge the gap between materials science and safe ...
Mariya L. Ivanova +4 more
wiley +1 more source
Toolkit to prompt and support stopping antidepressants in general practice: an interview study exploring patient participants' experiences in the RELEASE trial. [PDF]
Moura Ferreira P +3 more
europepmc +1 more source
Cell Segmentation Beyond 2D—A Review of the State‐of‐the‐Art
Cell segmentation underpins many biological image analysis tasks, yet most deep learning methods remain limited to 2D despite the inherently 3D nature of cellular processes. This review surveys segmentation approaches beyond 2D, comparing 2.5D and fully 3D methods, analyzing 31 models and 32 volumetric datasets, and introducing a unified reference ...
Fabian Schmeisser +6 more
wiley +1 more source
Reducing home infusion CLABSI through a dashboard and toolkit implementation. [PDF]
Hannum S +10 more
europepmc +1 more source
Harnessing Machine Learning to Understand and Design Disordered Solids
This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley +1 more source
The Coli Toolkit (CTK): An Extension of the Modular Yeast Toolkit for Use in <i>E. coli</i>. [PDF]
Mejlsted J +3 more
europepmc +1 more source

