A holistic framework for intradialytic hypotension prediction using generative adversarial networks-based data balancing.
Journal:
BMC medical informatics and decision making
Published Date:
Jul 10, 2025
Abstract
BACKGROUND: Intradialytic Hypotension (IDH) is a frequent complication in hemodialysis, yet predictive modeling is challenged by class imbalance. Traditional oversampling methods often struggle with complex clinical data. This study evaluates an enhanced conditional Wasserstein Generative Adversarial Network with Gradient Penalty (CWGAN-GP) framework to improve IDH prediction by generating high-utility synthetic data for balancing.
