Results 191 to 200 of about 476,790 (313)

Learning ontology axioms over knowledge graphs via representation learning

, 2019
This presents a representation learning model called SetE by modeling a predicate into a subspace in a semantic space where entities are vectors. Within SetE, a type as unary predicate is encoded as a set of vectors and a relation as binary predicate is ...
Wang, Z, Wang, K, Feng, Z, Zhang, X, Zhao, L   +4 more
core  

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

A Multimodal Representation Learning Framework for Molecular Graph and NMR Spectrum Alignment. [PDF]

Entropy (Basel)
Li X, Wang X, Liu ZM, Liu JB, Huang X.
europepmc   +1 more source

A Return to Normality: A Descriptive Qualitative Interview Study Exploring the Patient Experience of Gout Flare Resolution

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, Anne Horne, Angelo Gaffo, Lisa K. Stamp, N. Lawrence Edwards, Nicola Dalbeth   +5 more
wiley   +1 more source

A tri-modal contrastive learning framework for protein representation learning. [PDF]

Cell Rep Methods
Zhang L, Guo H, Schaffer L, Ko YS, Singh D, Rahmani H, Grotjahn D, Villa E, Gilson M, Wang W, Ideker T, Xing E, Xie P.   +12 more
europepmc   +1 more source

Frailty Predicts Incident Osteoporotic Fractures in Veterans with Rheumatoid Arthritis

Arthritis Care &Research, Accepted Article.
Background/Objective Rheumatoid arthritis (RA) is associated with an increased risk of frailty and osteoporosis, but the relationship between frailty and incident osteoporotic fractures in RA is underexplored. Methods Data were from the Veterans Affairs Rheumatoid Arthritis (VARA) Registry.
Katherine D. Wysham, Hannah F. Brubeck, Aaron Baraff, Punyasha Roul, Namrata Singh, James S. Andrews, Grant W. Cannon, Gary A. Kunkel, Ted R. Mikuls, Bryant R. England, Dolores M. Shoback, Patricia P. Katz, Jose M. Garcia, Ariela R. Orkaby, Joshua F. Baker   +14 more
wiley   +1 more source

The Impact of Cervical Cytology Category Imbalance on Self-Supervised Representation Learning. [PDF]

Comput Struct Biotechnol J
Liu S, Chang X, Bai J, Chen L, Zeng S, Quan T, Liucor X, Cheng S.   +7 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

Multilabel prediction of virus target proteins via multimodal graph representation learning. [PDF]

PLoS Comput Biol
Ma K, Liu K, Xin Y, Liu R.
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