DISCO-TAB: A Hierarchical Reinforcement Learning Framework for Privacy-Preserving Synthesis of Complex Clinical Data

DISCO-TAB: A Hierarchical Reinforcement Learning Framework for Privacy-Preserving Synthesis of Complex Clinical Data explores A hierarchical reinforcement learning framework for generating high-fidelity, privacy-preserving synthetic clinical data that significantly improves downstream classifier performance.. Commercial viability score: 7/10 in Synthetic Data Generation.