Results 251 to 260 of about 6,436,916 (343)

Applying Corrective Machine Learning in the E3SM Atmosphere Model in C++ (EAMxx) Dataset 1 of 12

Aaron S. Donahue
openalex   +1 more source

Retraction: An inherently interpretable deep learning model for local explanations using visual concepts. [PDF]

PLoS One
PLOS One Editors.
europepmc   +1 more source

Smart, Bio‐Inspired Polymers and Bio‐Based Molecules Modified by Zwitterionic Motifs to Design Next‐Generation Materials for Medical Applications

Advanced Functional Materials, EarlyView.
Bio‐based and (semi‐)synthetic zwitterion‐modified novel materials and fully synthetic next‐generation alternatives show the importance of material design for different biomedical applications. The zwitterionic character affects the physiochemical behavior of the material and deepens the understanding of chemical interaction mechanisms within the ...
Theresa M. Lutz, Jonas De Breuck, Sahar Salehi, Meike N. Leiske   +3 more
wiley   +1 more source

Applying Corrective Machine Learning in the E3SM Atmosphere Model in C++ (EAMxx) Dataset 11 of 12

Aaron S. Donahue
openalex   +1 more source

Development and validation of a machine learning model for predicting hypersplenism in Wilson disease patients. [PDF]

Front Med (Lausanne)
Xuan Q, Shi X, Jin L, Hua D, Sun L, Yang W, Wang H.   +6 more
europepmc   +1 more source

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, Cristiano Pesce, Antonietta Greco, Claudia Pisante, Greta Avancini, Valentina Di Francesco, Yosi Shamay, Paolo Decuzzi   +7 more
wiley   +1 more source

Physics-Informed Operator Learning for Parameter Estimation in Lithium-Ion-Battery Models Enhanced by Global Experimental Design and Local Identifiability Analysis

Philipp Brendel, Christopher Straub, Andreas Roßkopf, Vincent Lorentz, Felix Dietrich   +4 more
openalex   +1 more source

The Use of Production-based Learning Models to Improve Student Learning Outcomes in the Study of Carving Working Techniques on Skill Competence

, 2019
Ella Agustina
openalex   +2 more sources

Identification of KRAS mutation in rectal cancer based on a 2.5D deep learning model. [PDF]

Front Oncol
Zhang C, Li J, Chen P, Zhou Y, Shen J, Chen G.   +5 more
europepmc   +1 more source

Chemoselective Sequential Polymerization: An Approach Toward Mixed Plastic Waste Recycling

Advanced Functional Materials, EarlyView.
Inspired by biological protein metabolism, this study demonstrates the closed‐loop recycling of mixed synthetic polymers via ring‐closing depolymerization followed by a chemoselective sequential polymerizations process. The approach recovers pure polymers from mixed feedstocks, even in multilayer formats, highlighting a promising strategy to overcome a
Gadi Slor, Youwei Ma, Hyunwoo Park, Tae‐Lim Choi, Damien Guironnet, Francesco Stellacci   +5 more
wiley   +1 more source