Results 171 to 180 of about 26,485 (265)
Derivation and validation of a machine learning-driven score to predict the diagnostic yield of endomyocardial biopsy. [PDF]
Basile C +18 more
europepmc +1 more source
Objective JAK inhibitors (JAKis) have shown promising effects in early‐phase studies of SSc. We aimed to assess the safety and explore effectiveness of JAKis compared to conventional immunosuppressants in SSc. Methods A longitudinal retrospective study of the EUSTAR cohort was performed.
Stefano Di Donato +27 more
wiley +1 more source
Generalized Navier-Stokes model for ballistic and tomographic electrons. [PDF]
Estrada-Álvarez J +2 more
europepmc +1 more source
Frailty Predicts Incident Osteoporotic Fractures in Veterans with Rheumatoid Arthritis
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 +14 more
wiley +1 more source
Ceramide-based machine learning models for the diagnosis of unstable angina: a prospective multicenter study. [PDF]
Xie Z +12 more
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
Certified quantum randomness within purity constraints. [PDF]
Lin X, Wang R, Yin ZQ, Wang S.
europepmc +1 more source
Additive Gaussian Process Regression for Predictive Design of High‐Performance, Printable Silicones
A chemistry‐aware design framework for tuning printable polydimethylsiloxane (PDMS) for vat photopolymerization (VPP) is developed using additive Gaussian process (GP) modeling. Polymer network mechanics informs variable groupings, feasible formulation constraints, and interaction variables.
Roxana Carbonell +3 more
wiley +1 more source
Deriving connectivity from spiking activity in detailed models of large-scale cortical microcircuits. [PDF]
Moghbel F +4 more
europepmc +1 more source

