Artificial Intelligence Medical Compendium

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

Showing 24,701 to 24,710 of 217,472 articles

High-fidelity machine learning models for predicting antibacterial effects of cerium oxide nanoparticles across bacterial strains.

Discover nano
The primary objective of this study is to develop and validate robust data-driven models for accurately predicting bacterial growth inhibition induced by cerium oxide nanoparticles across different bacterial strains and experimental conditions. This ... read more 

Machine learning examination based on Bayesian regularized algorithm for slip effects on solarized Boger nanofluid with activation energy.

Discover nano
This model is highly helpful in thermal management and complex energy systems, particularly where precise control over heat and mass transfer is required. Solarized nanofluids can be used to improve heat absorption and transfer in solar thermal colle... read more 

Resolving the ambiguous binding site of quercetin at the calcineurin subunit junction using funnel metadynamics with deep learning collective variables.

Journal of computer-aided molecular design
Calcineurin represents a prominent target for immunosuppressive drugs, where conventional macrocyclic inhibitors utilize an immunophilin-dependent mechanism for their inhibition but are consequently hindered by adverse effects and variable pharmacoki... read more 

Optimizing Non-invasive Fractional Flow Reserve Estimation with Machine Learning-Enhanced 1D Hemodynamic Modeling.

Cardiovascular engineering and technology
Patient-specific computational models exhibit strong concordance with invasively measured fractional flow reserve (FFR)-the clinical gold standard for diagnosing coronary ischemia. However, current modeling techniques frequently rely on computational... read more 

Thermal analysis of bioconvection flow of CNTs/water based hybrid nanofluid with gyrotactic microbes using artificial neural network.

Discover nano
This study uses the Levenberg-Marquardt strategy with feed forward neural networks (LMS-FNN) to inspect the Soret-Dufour effect on radiative hybrid nanofluid flow across a Riga plate with gyrotactic microorganisms. The suggested model, which investig... read more 

A robust hybrid data driven approach to model biochar yield in terms of biomass pyrolysis.

Bioresources and bioprocessing
Biochar yield prediction plays a critical role in optimizing pyrolysis processes and advancing sustainable biomass utilization. This study introduces a hybrid machine learning framework that integrates Decision Tree models with four optimization stra... read more