Medicine/Public Health

HACHI is an iterative human-in-the-loop framework that utilizes AI agents to accelerate the development of fully interpretable clinical prediction models (CPMs) from unstructured clinical notes. By alternating between AI-driven statistical exploration and expert human feedback, the system optimizes for transparency and steerability, demonstrably outperforming traditional modeling approaches in tasks like acute kidney injury and traumatic … Read more

The Latest Era of High-Fidelity Synthetic Data: Beyond Simple Mimicry For years, the holy grail of data science has been the ability to share sensitive information—particularly in healthcare—without compromising individual privacy. Enter Tabular Generative Models (DGMs). Whereas early iterations of synthetic data often felt like “blurry” versions of the original, we are entering an era … Read more