A Comprehensive Machine Learning Framework for Predicting Blood-Brain Barrier Permeability Enhanced by Ant Colony Optimization

The ACO-Optimized DNN provides a highly accurate tool for virtual screening in CNS drug discovery, and the methodology serves as a generalizable template for complex model optimization.

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Publication Details

Journal
Current Drug Discovery Technologies
Published
2026-01-20
DOI
https://doi.org/10.2174/0115701638435141251208064507
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
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article

A Comprehensive Machine Learning Framework for Predicting Blood-Brain Barrier Permeability Enhanced by Ant Colony Optimization

Ahmed Miloudi, Said Boujraf, Mohamed Chikri
Current Drug Discovery Technologies
Computational Drug Discovery Methods
article

A Comprehensive Machine Learning Framework for Predicting Blood-Brain Barrier Permeability Enhanced by Ant Colony Optimization

Ahmed Miloudi, Said Boujraf, Mohamed Chikri
article en

Abstract

The ACO-Optimized DNN provides a highly accurate tool for virtual screening in CNS drug discovery, and the methodology serves as a generalizable template for complex model optimization.

Current Drug Discovery TechnologiesVol. 23
Sidi Mohamed Ben Abdellah University (MA)
Openalex Percentile: Top 74%
Computational Drug Discovery Methods
DOISourceOpenAlex
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A Comprehensive Machine Learning Framework for Predicting Blood-Brain Barrier Permeability Enhanced by Ant Colony Optimization — Ahmed Miloudi, Said Boujraf, et al. · Current Drug Discovery Technologies (2026) | TGRS Research Map | TGRS