Results 91 to 100 of about 183,671 (259)
Modern Management of Asymptomatic Carotid Stenosis: A Meta‐Analysis of CREST‐2, SPACE‐2, and ECST‐2
ABSTRACT Background Recent randomized trials (CREST‐2, SPACE‐2, and ECST‐2) have compared carotid revascularization (carotid endarterectomy [CEA] or carotid artery stenting [CAS]) plus contemporary medical therapy (CMT) versus CMT alone in asymptomatic carotid stenosis.
Aasim Ali +14 more
wiley +1 more source
White Matter and Perivascular Imaging Changes in Alzheimer's Disease and Cerebral Amyloid Angiopathy
ABSTRACT Objective Peak‐width of skeletonized mean diffusivity (PSMD) and diffusion tensor imaging–analysis along the perivascular space (DTI‐ALPS), reflecting white matter integrity and glymphatic function, are altered in Alzheimer's disease (AD).
Debina Laishram +3 more
wiley +1 more source
Objective This research article aims to describe the prevalence, associations, and health‐related quality of life (HRQoL) impact of mucocutaneous features of systemic lupus erythematosus (SLE). Methods Data from the Asia‐Pacific Lupus Collaboration cohort were analyzed (2013–2021).
Amanda M. Saracino +42 more
wiley +1 more source
The Role of Local Governments in the Transformation of Public Spaces: The Case of Atakum City Square
Beyond being physical spaces, public spaces are critical for social interaction and social integration. Local governments have great influence over public spaces due to their authority to regulate, improve and open these spaces for use.
Deniz YILDIZ USLU, Tuğçe ŞANLI KATI
doaj +1 more source
Objective For cartilage morphology to serve as a scalable endpoint in clinical trials, analyses should be performed automatically without human interaction. To clinically validate artificial intelligence (AI)‐based analysis, we studied cartilage loss from MRI prior to knee replacement.
Felix Eckstein +3 more
wiley +1 more source
dynoGP: Deep Gaussian Processes for Dynamic System Identification
This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli +3 more
wiley +1 more source
A unified research data management framework for heterogeneous materials data is presented. The system integrates multimodal datasets using ontologies and knowledge graphs, enabling interoperability and FAIR (findable, accessible, interoperable, reusable) data principles. By linking data across scales and workflows, it supports reproducible, Artifitial
Doaa Mohamed +6 more
wiley +1 more source
Fostering Innovation: Streamlining Magnetocaloric Materials Research by Digitalization
Magnetocaloric cooling (MCE) is an environmentally friendly refrigeration method with great potential. Optimizing MCE materials involves the preparation and screening of large quantities of samples, which in turn generates a large amount of data. A digitalization approach is presented that uses ontologies, knowledge graphs, and digital workflows to ...
Simon Bekemeier +17 more
wiley +1 more source
Given the escalating use of digital tools and the Internet of Things in public spaces for quality control, there is an imperative need to address the following question: How can cities enhance the adaptability of their public spaces in the face of ...
Fatemeh Badel +2 more
doaj +1 more source
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

