Enhancing Clinical Prediction via Synthetic Tabular Data Generation Using Deep Generative Models
The development of reliable machine learning (ML) models for clinical diagnosis is hindered by limited availability of large-scale, diverse, and high-quality medical datasets due to privacy constraints, class imbalance, and data heterogeneity. Synthetic data generation using deep generative models provides a promising...