Computational intelligence modeling of hyoscine drug solubility and solvent density in supercritical processing: gradient boosting, extra trees, and random forest models

Computational intelligence modeling of hyoscine drug solubility

Illustration of a decision tree.

Evaluation of Deep Learning Architectures for Aqueous Solubility

Computational intelligence modeling using Artificial Intelligence

Cluster-Based Regression Model for Predicting Aqueous Solubility

Advanced AI modeling and optimization for determination of

Pushing the limits of solubility prediction via quality-oriented

Computational intelligence modeling of hyoscine drug solubility

Evaluating uncertainty-based active learning for accelerating the

PDF) Computational intelligence modeling of hyoscine drug