Results 131 to 140 of about 35,242 (295)
Clinical, Histologic, and Serological Predictors of Renal Function Loss in Lupus Nephritis
Objective Kidney survival is the ultimate goal in lupus nephritis (LN) management, but long‐term predictors remain inadequately studied, requiring long‐term follow‐up. This study aimed to identify baseline and early longitudinal predictors of kidney survival in the Accelerating Medicines Partnership LN longitudinal cohort.
Shangzhu Zhang +21 more
wiley +1 more source
Objective Studies of damage accrual in patients with systemic lupus erythematosus (SLE) show associations with disease activity measured by the SLE Disease Activity Index 2000 (SLEDAI‐2K), but these associations are imperfect. SLEDAI scores are powerfully influenced by weightings (1–8) assigned to each domain.
Kevin Zhang +8 more
wiley +1 more source
Objective The objective of this article is to identify perceptions of patients with systemic lupus erythematosus (SLE) regarding artificial intelligence (AI)–based online symptom assessment tools, and the potential of these tools to address diagnostic barriers.
Olivia A. Stein +7 more
wiley +1 more source
Privacy-preserving explainable AI: a survey
As the adoption of explainable AI (XAI) continues to expand, the urgency to address its privacy implications intensifies. Despite a growing corpus of research in AI privacy and explainability, there is little attention on privacy-preserving model ...
Huynh, Thanh Trung +7 more
core +1 more source
Explainable AI in the military domain
AbstractArtificial intelligence (AI) has become nearly ubiquitous in modern society, from components of mobile applications to medical support systems, and everything in between. In societally impactful systems imbued with AI, there has been increasing concern related to opaque AI, that is, artificial intelligence where it is unclear how or why certain
openaire +1 more source
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
The stability criteria affecting the formation of high‐entropy alloys, particularly focusing in supersaturated solid solutions produced by mechanical alloying, are analyzed. Criteria based on Hume–Rothery rules are distinguished from those derived from thermodynamic relations. The formers are generally applicable to mechanically alloyed samples.
Javier S. Blázquez +5 more
wiley +1 more source
Building clinician trust in AI-assisted neurodiagnostics: A case-based evaluation
Neurodiagnostics and AI: How Artificial Intelligence is changing the Future of Neurodiagnostics. Clinician trust is critical for successfully adopting AI-assisted tools in clinical settings.
K.S.V. Angu Bala Ganesh +3 more
doaj +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 Knowledge‐Based Approach for Understanding and Managing Additive Manufacturing Data
Additive manufacturing processes generate a large amount of data. Effectively managing, understanding, and retrieving information from this data remains a major challenge. Therefore, we propose an ontology‐based approach to integrate heterogeneous data, enable semantic queries, and support decision‐making.
Mina Abd Nikooie Pour +5 more
wiley +1 more source

