Babels.AI

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About EHRSynth

EHRSynth is a synthetic data studio for clinical datasets. Upload any EHR-style CSV, and it infers column types and care stages (baseline, pre-op, intra-op, post-op, follow-up), removes identifiers, trains a stage-conditional diffusion model and generates synthetic patients you can download.

Each synthetic dataset is evaluated for fidelity (Wasserstein and total variation distance), privacy (membership inference, replica rate, attacker AUC) and utility (train on synthetic, test on real).

Input
Any clinical or tabular CSV.
Output
A downloadable synthetic dataset, 10 to 10,000 patients.
Model
Stage-conditional diffusion model with optional EMA and DP-style privacy regularization.
Evaluation
Attacker AUC, membership inference gap, replica rate, Wasserstein distance, TV distance and TSTR.

Research demonstration only. Not for clinical decision-making.