Craving Prediction From fMRI Drug Cue Reactivity in Methamphetamine Use Disorder: A Parsimonious Neurobiological Model.

ABSTRACT:

Background

Craving is a fundamental aspect of substance use disorder (SUD), traditionally assessed through subjective self-report measures. To develop more objective assessments, we created a brain-based marker to predict craving based on machine learning approaches using functional magnetic resonance imaging (fMRI) drug cue reactivity data from 69 participants with methamphetamine use disorders.

Methods

To predict craving intensity (rated on a 1-4 scale), we developed a modeling pipeline in which multiple feature selection methods (ANOVA, PCA) and regression algorithms (linear regression, Lasso, Elastic Net, Random Forest, and XGBoost) were evaluated. Model performance was assessed using subject-level 5-fold cross-validation plus a 20% hold-out test set. PCA combined with l

SUBMITTER: Mahdavi-Doost H 

PROVIDER: S-EPMC12537833 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature