Results 151 to 160 of about 88,434 (216)

Early prediction of gestational diabetes mellitus with clinical characteristics, cell-free DNA and genetic variants. [PDF]

J Transl Med
Chen S, Wang L, Zhu Q, Wang F, Tang C, Zhang B, Shi Y, Liu M, Liu C, Wang Y, Cao X, Cheng M, Peng M, Yuan Y, Kong L, Liang B, Shi Z, Huang H, Xu C, Wu Y.   +19 more
europepmc   +1 more source

Artificial Intelligence in Systemic Sclerosis: Clinical Applications, Challenges, and Future Directions

Arthritis Care &Research, EarlyView.
Systemic sclerosis (SSc) is a rare autoimmune disease defined by immune dysregulation, vasculopathy, and progressive fibrosis of the skin and internal organs. Despite advances in care, major complications such as interstitial lung disease (ILD) and myocardial involvement remain the leading causes of morbidity and mortality.
Cristiana Sieiro Santos, José Miguel Sequí‐Sabater, Diego Benavent   +2 more
wiley   +1 more source

Experiments with optimal model trees. [PDF]

Sci Rep
Roselli SF, Frank E.
europepmc   +1 more source

Beyond Visual Scoring: Computational CT‐analysis for HRCT based quantification of Interstitial Lung Disease in Inflammatory Rheumatic Disease

Arthritis Care &Research, Accepted Article.
Interstitial lung disease (IRD‐ILD) is a significant cause of morbidity and mortality in patients with inflammatory rheumatic disorders (IRD). High‐resolution computed tomography (HRCT) is widely considered the gold standard for the non‐invasive assessment of ILD; however, its interpretation is constrained by substantial inter‐observer variability and ...
Alexander Pfeil, Tobias Hoffmann, Ulf Teichgräber, Diane Renz, Denise Beckmann, Gunter Wolf, Nicole Schadewaldt, Bianca Lassen‐Schmidt   +7 more
wiley   +1 more source

Beyond Beer-Lambert Linear Regression: Multi-Layer Modeling for Wide-Range Concentration Quantification Using Ultraviolet-visible Spectroscopy. [PDF]

Anal Sci Adv
ALjifri M, Miller C, Qian Y, Chen Y, Jiang M.   +4 more
europepmc   +1 more source

A Q‐Learning Algorithm to Solve the Two‐Player Zero‐Sum Game Problem for Nonlinear Systems

International Journal of Adaptive Control and Signal Processing, Volume 39, Issue 3, Page 566-581, March 2025.
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, Anthony Siming Chen, Guido Herrmann   +2 more
wiley   +1 more source

Markov chain-based turnout state prediction and lifespan simulation. [PDF]

Sci Rep
Wu Z, He W, Wu Z, Gu S, Li C, Guo J.
europepmc   +1 more source

Characterization of Defect Distribution in an Additively Manufactured AlSi10Mg as a Function of Processing Parameters and Correlations with Extreme Value Statistics

Advanced Engineering Materials, EarlyView.
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, Varma Kvvssn, Hossein Laieghi, Zia Uddin, Peyman Ansari, E. Kıvanç Sadak, Can Barış Toprak, Hüseyin Kızıl, Enrico Salvati   +8 more
wiley   +1 more source

Enhancing Manufacturing Cell Formation Through Availability-Based Optimization Using the Black Widow Optimizer Metaheuristic. [PDF]

Biomimetics (Basel)
Figueroa-Torrez P, Duran O, Crawford B, Cisternas-Caneo F.   +3 more
europepmc   +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, Thomas Wallmersperger, Gianaurelio Cuniberti   +2 more
wiley   +1 more source