Results 161 to 170 of about 15,936,409 (281)
Patients improve, patterns persist: longitudinal stability of RA joint involvement patterns
Objective Rheumatoid arthritis is a heterogeneous disease. Data‐driven approaches, from synovial histology to joint involvement patterns (JIPs), have sought to define clinically meaningful subgroups. Whether these subgroups represent stable phenotypes or transient disease states remains unclear.
Tjardo Maarseveen +24 more
wiley +1 more source
Objective We examined associations of post‐traumatic stress disorder (PTSD) and other mental health disorders (OMH) with rheumatoid arthritis (RA), accounting for effects of smoking. Methods We conducted a matched case‐control study, identifying incident RA cases and controls using national Veteran Health Administration data (2006‐2019).
Kelsey Coziahr +15 more
wiley +1 more source
A novel method based on ultrasound radiomics for predicting attainment of near-adult height in adolescents. [PDF]
Zhang Y +8 more
europepmc +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
Clinical evaluation and predictive model development of AI-based non-invasive embryo selection in <i>in vitro</i> fertilization patients. [PDF]
Zhu P, Bi X, Su D, Zhang X, Wu X.
europepmc +1 more source
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt +8 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
Early Risk Stratification of Severe Trauma in the Emergency Department: Integrating Clinical Scoring Systems, Dynamic Biomarkers, and Artificial Intelligence-A Narrative Review. [PDF]
Sun X, Han J, Ni J, Shen Y.
europepmc +1 more source
Z score neurofeedback : clinical applications /
Neurofeedback is utilized by over 10,000 clinicians worldwide with new techniques and uses being found regularly. Z Score Neurofeedback is a new technique using a normative database to identify and target a specific individual's area of dysregulation ...
Lubar, Joel F.,editor. +2 more
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