AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Permeability

Showing 31 to 40 of 65 articles

Clear Filters

Effects of Microabrasion Prior to In-office Bleaching on Hydrogen Peroxide Permeability, Color Change, and Enamel Morphology.

Operative dentistry
PURPOSE: This study evaluated hydrogen peroxide (HP) diffusion within the pulp chamber, as well as color change and the surface morphology of teeth subjected to various microabrasion (MA) protocols associated or not with in-office (IO) bleaching.

Towards Deep Neural Network Models for the Prediction of the Blood-Brain Barrier Permeability for Diverse Organic Compounds.

Molecules (Basel, Switzerland)
Permeation through the blood-brain barrier (BBB) is among the most important processes controlling the pharmacokinetic properties of drugs and other bioactive compounds. Using the fragmental (substructural) descriptors representing the occurrence num...

Artificial neural network approach for predicting blood brain barrier permeability based on a group contribution method.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The purpose of this study was to develop a quantitative structure-activity relationship (QSAR) model for the prediction of blood brain barrier (BBB) permeability by using artificial neural networks (ANN) in combination with ...

Prediction of the Blood-Brain Barrier (BBB) Permeability of Chemicals Based on Machine-Learning and Ensemble Methods.

Chemical research in toxicology
The ability of chemicals to enter the blood-brain barrier (BBB) is a key factor for central nervous system (CNS) drug development. Although many models for BBB permeability prediction have been developed, they have insufficient accuracy (ACC) and sen...

Revolutionizing Membrane Design Using Machine Learning-Bayesian Optimization.

Environmental science & technology
Polymeric membrane design is a multidimensional process involving selection of membrane materials and optimization of fabrication conditions from an infinite candidate space. It is impossible to explore the entire space by trial-and-error experimenta...

Ensemble modeling with machine learning and deep learning to provide interpretable generalized rules for classifying CNS drugs with high prediction power.

Briefings in bioinformatics
The trade-off between a machine learning (ML) and deep learning (DL) model's predictability and its interpretability has been a rising concern in central nervous system-related quantitative structure-activity relationship (CNS-QSAR) analysis. Many st...

DeepBBBP: High Accuracy Blood-brain-barrier Permeability Prediction with a Mixed Deep Learning Model.

Molecular informatics
Blood-brain-barrier permeability (BBBP) is an important property that is used to establish the drug-likeness of a molecule, as it establishes whether the molecule can cross the BBB when desired. It also eliminates those molecules which are not suppos...

Trivariate Linear Regression and Machine Learning Prediction of Possible Roles of Efflux Transporters in Estimated Intestinal Permeability Values of 301 Disparate Chemicals.

Biological & pharmaceutical bulletin
A system for predicting apparent bidirectional permeability (P) across Caco-2 cells of diverse chemicals has been reported. The present study aimed to investigate the relationship between in silico-generated P (from apical to basal side, P) for 301 s...

Relational graph convolutional networks for predicting blood-brain barrier penetration of drug molecules.

Bioinformatics (Oxford, England)
MOTIVATION: Evaluating the blood-brain barrier (BBB) permeability of drug molecules is a critical step in brain drug development. Traditional methods for the evaluation require complicated in vitro or in vivo testing. Alternatively, in silico predict...

High-Fidelity Permeability and Porosity Prediction Using Deep Learning With the Self-Attention Mechanism.

IEEE transactions on neural networks and learning systems
Accurate estimation of reservoir parameters (e.g., permeability and porosity) helps to understand the movement of underground fluids. However, reservoir parameters are usually expensive and time-consuming to obtain through petrophysical experiments o...