Results 201 to 210 of about 385,160 (293)

Distinct Systemic Sclerosis Phenotypes Related to Ethnicity: An Opportunity to Personalize Care?

Arthritis Care &Research, EarlyView.
Objective The objective is to describe and compare demographic, clinical, and serological characteristics of patients with systemic sclerosis (SSc) according to ethnic background. Methods Participants enrolled in the Canadian Scleroderma Research Group cohort who self‐identified to a single ethnicity group were included.
Danick Goulet, Camille Guertin, Maggie Larché, Isabelle Ferdinand, Marie Hudson, May Y. Choi, Mohammed Osman, Janet Pope, Carter Thorne, Murray Baron, Sasha Bernatsky, Sabrina Hoa   +11 more
wiley   +1 more source

Joint mirror procedure: controlling false discovery rate for identifying simultaneous signals. [PDF]

Biometrics
Deng L, He K, Zhang X.
europepmc   +1 more source

FDRestimation: Flexible False Discovery Rate Computation in R. [PDF]

F1000Res, 2021
Murray MH, Blume JD.
europepmc   +1 more source

Real‐World Safety and Effectiveness of JAK Inhibitors in Systemic Sclerosis: A Propensity‐Matched Study from the EUSTAR Cohort

Arthritis Care &Research, Accepted Article.
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, Marie‐Elise Truchetet, Marco Minerba, Oliver Distler, Juan José Alegre Sancho, Yolanda Braun‐Moscovici, Christina Bergmann, Petros Sfikakis, Jeska K de Vries‐Bouwstra, Murray Baron, Silvia Bellando‐Randone, Lorenzo Dagna, Christopher P Denton, Madelon C Vonk, Vanessa Smith, Ivan Castellvi, Gabriela Riemekasten, Andra Balanescu, Masataka Kuwana, Maria De Santis, Kamal Solanki, Anastas Batalov, Vahan Mukuchyan, Marco Matucci‐Cerinic, Yannick Allanore, Francesco Del Galdo, Michael Hughes, EUSTAR Collaborators   +27 more
wiley   +1 more source

Controlling false discovery rate for mediator selection in high-dimensional data. [PDF]

Biometrics
Dai R, Li R, Lee S, Liu Y.
europepmc   +1 more source

OPTIMAL FALSE DISCOVERY RATE CONTROL FOR LARGE SCALE MULTIPLE TESTING WITH AUXILIARY INFORMATION. [PDF]

Ann Stat, 2022
Cao H, Chen J, Zhang X.
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

mulea: An R package for enrichment analysis using multiple ontologies and empirical false discovery rate. [PDF]

BMC Bioinformatics
Turek C, Ölbei M, Stirling T, Fekete G, Tasnádi E, Gul L, Bohár B, Papp B, Jurkowski W, Ari E.   +9 more
europepmc   +1 more source

DIAMetAlyzer allows automated false-discovery rate-controlled analysis for data-independent acquisition in metabolomics. [PDF]

Nat Commun, 2022
Alka O, Shanthamoorthy P, Witting M, Kleigrewe K, Kohlbacher O, Röst HL.   +5 more
europepmc   +1 more source

Additive Gaussian Process Regression for Predictive Design of High‐Performance, Printable Silicones

Advanced Engineering Materials, EarlyView.
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, Martha Leach, Hongtao Song, Carolyn Seepersad   +3 more
wiley   +1 more source