Simulated Blood Alcohol Concentration (BAC) Dataset for Machine Learning Prediction Using a Two-Compartment Pharmacokinetic Model
Abstract
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
Fields of Study & Subjects
Alcohol Consumption and Health Effects
Artificial Intelligence in Healthcare
Forensic Toxicology and Drug Analysis
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 11 March 2026
- Language
- EN
- Document type
- Dataset