Simulated Blood Alcohol Concentration (BAC) Dataset for Machine Learning Prediction Using a Two-Compartment Pharmacokinetic Model

This dataset contains simulated blood alcohol concentration (BAC) values generated from a physiologically informed two-compartment pharmacokinetic model describing alcohol absorption and elimination kinetics. The dataset was created to train and evaluate a Random Forest regression model for predicting BAC levels. Parameters were varied across physiologically informed ranges to generate a high-resolution dataset including degenerate and non-degenerate cases. The dataset supports the study on simulation-guided machine learning for biomedical kinetic modelin