Workflows Allowing Creation of Journal Article Supporting Information and Findable, Accessible, Interoperable, and Reusable (FAIR)-Enabled Publication of Spectroscopic Data. [PDF]
ACS Omega, 2019 Barba A +6 more
europepmc +1 more source
Arthritis Care &Research, EarlyView.Objective We assessed the effectiveness of PrismRA to improve clinical outcomes among patients with rheumatoid arthritis (RA) initiating treatment with a biologic or targeted synthetic disease‐modifying antirheumatic drug (b/tsDMARD). Methods PrismRA incorporated 19 gene expression features and four clinical features to assess a patient's likelihood of
Fenglong Xie +3 more
wiley +1 more source
Introducing article numbering to Journal of Empirical Finance
, 2023 Lianne van der Zant
openalex +1 more source
Generative artificial intelligence tools in journal article preparation: A preliminary catalog of ethical considerations, opportunities, and pitfalls. [PDF]
JDS CommunWhite RR.
europepmc +1 more source
Immediate Application of Knowledge Gained: From Journal Article to Improved Patient Care-Important Patient Clues Trainees May Be Missing. [PDF]
J Grad Med Educ, 2017 Viswanath O.
europepmc +1 more source
Reviewing Reviews: An Evaluation of Peer Reviews of Journal Article Submissions
, 2018 Laura J. Falkenberg, P. Soranno
semanticscholar +1 more source
Advanced Engineering Materials, EarlyView.This article presents the NFDI‐MatWerk Ontology (MWO), a Basic Formal Ontology‐based framework for interoperable research data management in materials science and engineering (MSE). Covering consortium structures, research data management resources, services, and instruments, MWO enables semantic integration, Findable, Accessible, Interoperable, and ...
Hossein Beygi Nasrabadi +4 more
wiley +1 more source
Are Overall Journal Rankings a Good Mapping for Article Quality in Specialty Fields?
, 2015 Melody Lo, Yong Bao
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Unleashing the Power of Machine Learning in Nanomedicine Formulation Development
Advanced Functional Materials, EarlyView.A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore +7 more
wiley +1 more source