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Chemical Phenomena

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Impact of Tagatose on Physicochemical, Nutritional, and In Vitro Digestive Properties of Toast Bread.

Journal of food science
It is more attractive to develop effective strategies to reduce sugar intake without compromising food quality with the rising prevalence of obesity and diabetes around the world. Due to its high cost, tagatose has not been widely adopted as a sucros...

Statistical evaluation of testing conditions on the saturated hydraulic conductivity of Brazilian lateritic soils using artificial intelligence approaches.

Scientific reports
The saturated hydraulic conductivity, k, is a crucial variable to describe the hydromechanical behavior of soils. The value of k of lateritic soils that are typically found in tropical regions is highly affected by the soil's structure, void ratio, a...

Prediction of hydrophilic and hydrophobic hydration structure of protein by neural network optimized using experimental data.

Scientific reports
The hydration structures of proteins, which are necessary for their folding, stability, and functions, were visualized using X-ray and neutron crystallography and transmission electron microscopy. However, complete visualization of hydration structur...

MetaSpot: A General Approach for Recognizing the Reactive Atoms Undergoing Metabolic Reactions Based on the MetaQSAR Database.

International journal of molecular sciences
The prediction of drug metabolism is attracting great interest for the possibility of discarding molecules with unfavorable ADME/Tox profile at the early stage of the drug discovery process. In this context, artificial intelligence methods can genera...

Recent Studies of Artificial Intelligence on Drug Absorption.

Journal of chemical information and modeling
Absorption is an important area of research in pharmacochemistry and drug development, because the drug has to be absorbed before any drug effects can occur. Furthermore, the ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) profi...

Chemprop: A Machine Learning Package for Chemical Property Prediction.

Journal of chemical information and modeling
Deep learning has become a powerful and frequently employed tool for the prediction of molecular properties, thus creating a need for open-source and versatile software solutions that can be operated by nonexperts. Among the current approaches, direc...

Mechanochemical Degradation of Biopolymers.

Molecules (Basel, Switzerland)
Mechanochemical treatment of various organic molecules is an emerging technology of green processes in biofuel, fine chemicals, or food production. Many biopolymers are involved in isolating, derivating, or modifying molecules of natural origin. Mech...

From NMR to AI: Designing a Novel Chemical Representation to Enhance Machine Learning Predictions of Physicochemical Properties.

Journal of chemical information and modeling
A novel approach to the utilization of nuclear magnetic resonance (NMR) spectroscopy data in the prediction of logD through machine learning algorithms is shown. In the analysis, a data set of 754 chemical compounds, organized into 30 clusters, was e...

Harnessing the Power of Machine Learning Guided Discovery of NLRP3 Inhibitors Towards the Effective Treatment of Rheumatoid Arthritis.

Cells
The NLRP3 inflammasome, plays a critical role in the pathogenesis of rheumatoid arthritis (RA) by activating inflammatory cytokines such as IL1β and IL18. Targeting NLRP3 has emerged as a promising therapeutic strategy for RA. In this study, a multid...

MPCD: A Multitask Graph Transformer for Molecular Property Prediction by Integrating Common and Domain Knowledge.

Journal of medicinal chemistry
Molecular property prediction with deep learning often employs self-supervised learning techniques to learn common knowledge through masked atom prediction. However, the common knowledge gained by masked atom prediction dramatically differs from the ...