Results 161 to 170 of about 103,585 (306)
A novel rule-based oversampling approach for imbalanced data classification
, 2023 When confronted with imbalanced datasets, traditional classifiers frequently struggle to correctly categorize samples from the minority class, adversely impacting the overall predictive performance of machine learning models.
Zhang, Xiao +2 more
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Arthritis Care &Research, EarlyView.Objective The concern that nonsteroidal anti‐inflammatory drugs (NSAIDs) may precipitate flares of inflammatory bowel disease (IBD) has limited their use in managing musculoskeletal symptoms in those with IBD, but safety data are mixed. Methods This retrospective cohort study included patients with IBD aged at least 18 years from Optum's deidentified ...
Adam S. Mayer +4 more
wiley +1 more source
Arthritis Care &Research, EarlyView.Over the past 50 years, the science of pediatric rheumatology has grown exponentially due to an expansion in the understanding of complex rheumatic conditions and a surge in novel targeted therapeutics. Physician‐scientists in the field of pediatric rheumatology have played major roles in these advancements that have improved the care of children ...
Ekemini A. Ogbu +2 more
wiley +1 more source
Arthritis Care &Research, EarlyView.Objective Although the definition of a gout flare is well established, the state of gout flare resolution has not yet been defined. This study aimed to explore patients’ experiences and perceptions of gout flare resolution. Methods Semistructured interviews were conducted with 24 people with gout, guided by open‐ended questions exploring their ...
Sarah Stewart +5 more
wiley +1 more source
β‐Catenin/c‐Myc Axis Modulates Autophagy Response to Different Ammonia Concentrations
Advanced Biology, Volume 9, Issue 3, March 2025.Ammonia, detoxified by the liver into urea and glutamine, impacts autophagy differently at varying levels. Low ammonia activates autophagy via c‐Myc and β‐catenin, while high levels suppress it. Using Huh7 cells and Spf‐ash mice, c‐Myc's role in cytoprotective autophagy is revealed, offering insights into hyperammonemia and potential therapeutic ...
S. Sergio +11 more
wiley +1 more source
What Do Large Language Models Know About Materials?
Advanced Engineering Materials, EarlyView.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
Learning from imbalanced and heterogeneous data
, 2017 Big data analysis is a term describing the analysis of large and/or complex datasets using a series of techniques including but not limited to machine learning techniques. Contemporary digital world comprises multiple forms of unstructured and/or semi-structured data that are inter-linked and inter-related in complex networks.
openaire +2 more sources
Advanced Engineering Materials, EarlyView.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
Advanced Engineering Materials, EarlyView.Selenium was incorporated into a sol–gel‐derived bioactive glass to enable sustained therapeutic ion release. The selenium‐containing glass preserved bioactivity while selectively inducing cytotoxicity in osteosarcoma cells and maintaining osteoblastic viability.
Breno Rocha Barrioni +7 more
wiley +1 more source
Probabilistic combination of static and dynamic gait features for verification
, 2005 This paper describes a novel probabilistic framework for biometric identification and data fusion. Based on intra and inter-class variation extracted from training data, posterior probabilities describing the similarity between two feature vectors may be
Bazin, Alex I., Nixon, Mark S.
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