Learning Between the Lines: Anaesthetists' Conceptions of the Implicit Curriculum in Postgraduate Education. [PDF]
Chin H +3 more
europepmc +1 more source
The authors evaluated six machine‐learned interatomic potentials for simulating threshold displacement energies and tritium diffusion in LiAlO2 essential for tritium production. Trained on the same density functional theory data and benchmarked against traditional models for accuracy, stability, displacement energies, and cost, Moment Tensor Potential ...
Ankit Roy +8 more
wiley +1 more source
Advanced Competencies for Endoscopy Nurses: A Rapid Review of Current Practices and Training Approaches. [PDF]
Minciullo A +4 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
Cultural Adaptation and Implementation Strategy of a Recovery-Oriented Mental Health Training Intervention (REFOCUS-THAIREC) for Healthcare Workers in Thailand: An Experience-Based Co-Design. [PDF]
Inta N, Grealish A, Leamy M.
europepmc +1 more source
Large Language Model‐Based Chatbots in Higher Education
The use of large language models (LLMs) in higher education can facilitate personalized learning experiences, advance asynchronized learning, and support instructors, students, and researchers across diverse fields. The development of regulations and guidelines that address ethical and legal issues is essential to ensure safe and responsible adaptation
Defne Yigci +4 more
wiley +1 more source
Environmental Sustainability Profile of Intensive Care Nurses in Türkiye: A Cross-Sectional Study. [PDF]
Erdem T +6 more
europepmc +1 more source
A Hybrid Transfer Learning Framework for Brain Tumor Diagnosis
A novel hybrid transfer learning approach for brain tumor classification achieves 99.47% accuracy using magnetic resonance imaging (MRI) images. By combining image preprocessing, ensemble deep learning, and explainable artificial intelligence (XAI) techniques like gradient‐weighted class activation mapping and SHapley Additive exPlanations (SHAP), the ...
Sadia Islam Tonni +11 more
wiley +1 more source
Four decades of retinal vessel segmentation research (1982–2025) are synthesized, spanning classical image processing, machine learning, and deep learning paradigms. A meta‐analysis of 428 studies establishes a unified taxonomy and highlights performance trends, generalization capabilities, and clinical relevance.
Avinash Bansal +6 more
wiley +1 more source
Valuing Place in Rural Health Education and Research: The Contribution of University Departments of Rural Health. [PDF]
Harvey P +3 more
europepmc +1 more source

