Results 81 to 90 of about 785,617 (209)
Unleashing the Power of Machine Learning in Nanomedicine Formulation Development
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
Building decision trees based on production knowledge as support in decision-making process
The article presents sources of production knowledge and thoroughly describes its identification which on the construction of decision trees, and on the construction of knowledge bases for production processes.
Matuszny Marcin
doaj +1 more source
Predicting Atomic Charges in MOFs by Topological Charge Equilibration
An atomic charge prediction method is presented that is able to accurately reproduce ab‐initio‐derived reference charges for a large number of metal–organic frameworks. Based on a topological charge equilibration scheme, static charges that fulfill overall neutrality are quickly generated.
Babak Farhadi Jahromi +2 more
wiley +1 more source
ACC forms via aggregating prenucleation clusters that gatekeep its chemical composition. Ion identity steers the path: Ba and Sr substitute Ca in clusters, thereby inhibiting nucleation, with a dose‐dependent switch of Sr to induction. Mg partitions into Mg‐rich and Mg‐poor clusters; the latter form ACC, expelling Mg.
Qianyu Zhao +9 more
wiley +1 more source
Computational Modeling Meets 3D Bioprinting: Emerging Synergies in Cardiovascular Disease Modeling
Emerging advances in three‐dimensional bioprinting and computational modeling are reshaping cardiovascular (CV) research by enabling more realistic, patient‐specific tissue platforms. This review surveys cutting‐edge approaches that merge biomimetic CV constructs with computational simulations to overcome the limitations of traditional models, improve ...
Tanmay Mukherjee +7 more
wiley +1 more source
A Novel Hyperparameter-Free Approach to Decision Tree Construction That Avoids Overfitting by Design
Decision trees are an extremely popular machine learning technique. Unfortunately, overfitting in decision trees still remains an open issue that sometimes prevents achieving good performance.
Rafael Garcia Leiva +3 more
doaj +1 more source
Robust Decision Trees Against Adversarial Examples
Although adversarial examples and model robustness have been extensively studied in the context of linear models and neural networks, research on this issue in tree-based models and how to make tree-based models robust against adversarial examples is ...
Boning, Duane +3 more
core
An Edible H2O2 Biosensor for Gastrointestinal Metabolites and Peroxidase Enzyme Quantification
We present an edible biosensor for gastric fluid analysis that integrates a caffeic acid–horseradish peroxidase redox system into an edible electrolyte‐gated transistor. The device enables rapid, low‐volume detection of H2O2 and, with minimal modification, metabolites and enzyme activity in simulated gastrointestinal conditions.
Valerio Francesco Annese +10 more
wiley +1 more source
Shopping intention prediction using decision trees
Introduction: The price is considered to be neglected marketing mix element due to the complexity of price management and sensitivity of customers on price changes. It pulls the fastest customer reactions to that change.
Dario Šebalj +2 more
doaj
This work introduces photo‐crosslinkable tyraminated poly(vinyl alcohol)‐gelatin (PVA‐GT) hydrogels as tunable injectable platforms for tissue engineering and growth factor delivery applications. This schematic illustrates the two developed hydrogel formulations and the experimental workflow used to evaluate their physico‐chemical properties in vitro ...
Alessia Longoni +15 more
wiley +1 more source

