Results 111 to 120 of about 977,116 (306)
This review summarizes artificial intelligence (AI)‐supported nonpharmacological interventions for adults with chronic rheumatic diseases, detailing their components, purpose, and current evidence base. We searched Embase, PubMed, Cochrane, and Scopus databases for studies describing AI‐supported interventions for adults with chronic rheumatic diseases.
Nirali Shah +5 more
wiley +1 more source
Objective The purpose was to evaluate a biomarker score consisting of MUC5B rs35705950 promoter variant, plasma matrix metalloproteinase (MMP)‐7, and serum anti‐malondialdehyde‐acetaldehyde (anti‐MAA) antibody for RA‐associated interstitial lung disease risk stratification. Methods Using a multicenter cohort of US veterans with RA, we performed a cross‐
Kelsey Coziahr +16 more
wiley +1 more source
The effect of chemical representation on active machine learning towards closed-loop optimization
Alexander Pomberger +8 more
openalex +2 more sources
Modeling PROTAC degradation activity with machine learning
13 pages, 10 ...
Stefano Ribes +3 more
openaire +3 more sources
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
This article provides an overview of recent advancements in bulk processing of rare‐earth‐free hard magnetic materials. It also addresses related simulation approaches at different scales. The research on rare‐earth‐free magnetic materials has increased significantly in recent years, driven by supply chain issues, environmental and social concerns, and
Daniel Scheiber, Andrea Bachmaier
wiley +1 more source
Active labour market policies for the long-term unemployed: New evidence\n from causal machine learning [PDF]
Daniel Göller +3 more
openalex +1 more source
The layer‐by‐layer (LbL) assembly of coordination solids, enabled by the surface‐mounted metal‐organic framework (SURMOF) platform, is on the cusp of generating the organic counterpart of the epitaxy of inorganics. The programmable and sequential SURMOF protocol, optimized by machine learning (ML), is suited for accessing high‐quality thin films of ...
Zhengtao Xu +2 more
wiley +1 more source
Biofabrication aims at providing innovative technologies and tools for the fabrication of tissue‐like constructs for tissue engineering and regenerative medicine applications. By integrating multiple biofabrication technologies, such as 3D (bio) printing with fiber fabrication methods, it would be more realistic to reconstruct native tissue's ...
Waseem Kitana +2 more
wiley +1 more source

