Results 151 to 160 of about 1,257,183 (296)
Objective To evaluate utility of an artificial intelligence (AI) health coach for systemic sclerosis (SSc) self‐management and identify patterns associated with participant engagement. Methods We conducted a mixed methods study in which an AI health coach, powered by a large language model (LLM), was used to support self‐management for SSc.
Nirali Shah +4 more
wiley +1 more source
Caregiver Perspectives on the Burden of Disease and Treatment in Uncontrolled Gout
Objective Uncontrolled gout (UG) refers to persistently elevated serum urate (SU) levels >6 mg/dL and ongoing gout symptoms despite use of urate‐lowering therapy (ULT). The objective of this study was to evaluate the burden associated with informal caregiving for individuals with UG.
Angelo Gaffo +6 more
wiley +1 more source
Survival Outcomes in Older Adults with Axial Spondyloarthritis and Concomitant Cancer
Objective The objective of this study was to determine survival outcomes in older adults with axial spondyloarthritis (axSpA) and concomitant cancer. Methods We conducted a population‐based study using Medicare claims data linked to Surveillance, Epidemiology, and End Results data to determine overall survival (OS) and cancer‐specific survival (CSS) in
Savannah Bowman +7 more
wiley +1 more source
In a highly automated Flexible Manufacturing System (FMS), optimal utilization and scheduling of resources and equipment are paramount. This necessity underpins the full utilization of automation capabilities, leading to increased productivity and ...
Erlianasha Samsuria +5 more
doaj
A Q‐Learning Algorithm to Solve the Two‐Player Zero‐Sum Game Problem for Nonlinear Systems
A Q‐learning algorithm to solve the two‐player zero‐sum game problem for nonlinear systems. ABSTRACT This paper deals with the two‐player zero‐sum game problem, which is a bounded L2$$ {L}_2 $$‐gain robust control problem. Finding an analytical solution to the complex Hamilton‐Jacobi‐Issacs (HJI) equation is a challenging task.
Afreen Islam +2 more
wiley +1 more source
What Do Large Language Models Know About Materials?
If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer +2 more
wiley +1 more source
Job Scheduling with Efficient Resource Monitoring in Cloud Datacenter. [PDF]
Loganathan S, Mukherjee S.
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
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
A genetic algorithm-based job scheduling model for big data analytics. [PDF]
Lu Q, Li S, Zhang W, Zhang L.
europepmc +1 more source

