MuhangTian/TimeDiff
Code to generate realistic synthetic healthcare data with diffusion models
This project helps healthcare researchers and data scientists generate realistic, synthetic electronic health record (EHR) time series data. You input existing de-identified EHR data, and it outputs new, artificial EHR data that maintains statistical properties and privacy. This is for professionals who need to develop and test models without compromising patient confidentiality.
No commits in the last 6 months.
Use this if you need to create privacy-preserving synthetic healthcare data for research, model development, or collaboration without sharing real patient information.
Not ideal if you need to generate synthetic data for domains outside of healthcare time series or require simple tabular data synthesis.
Stars
31
Forks
6
Language
Jupyter Notebook
License
—
Category
Last pushed
Apr 26, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/diffusion/MuhangTian/TimeDiff"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
huggingface/diffusers
🤗 Diffusers: State-of-the-art diffusion models for image, video, and audio generation in PyTorch.
bghira/SimpleTuner
A general fine-tuning kit geared toward image/video/audio diffusion models.
mcmonkeyprojects/SwarmUI
SwarmUI (formerly StableSwarmUI), A Modular Stable Diffusion Web-User-Interface, with an...
nateraw/stable-diffusion-videos
Create 🔥 videos with Stable Diffusion by exploring the latent space and morphing between text prompts
TheDesignFounder/DreamLayer
Benchmark diffusion models faster. Automate evals, seeds, and metrics for reproducible results.