AI & ML interests

healthcare AI, clinical NER, biomedical NLP, PII / de-identification, on-device AI, edge inference, Apple Silicon / MLX, data sovereignty, privacy-preserving ML, open-source

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OpenMed — open-source medical AI

Health × AI

Open clinical NER & PII de-identification models — private, local-first, on-device.

Models PyPI arXiv License Docs

Runs locally — in Python, on iOS and Android, in the browser, and on your own servers.


OpenMed ships a large, growing family of open medical-AI models: clinical named-entity recognition (diseases, chemicals, genes, anatomy, pharmacology, oncology) and privacy-preserving PII de-identification in 35 model-backed languages (42 supported language codes). The SDK and 2,200+ of the models are Apache-2.0, benchmark-driven, and small enough to run locally.

Start here

  • Browse the models → the tabs above (2,200+ NER & PII models)
  • Flagship clinical NER → OpenMed-NER-PharmaDetect-SuperClinical-434M
  • Python → pip install openmed
  • On-device → Swift OpenMedKit + MLX on Apple devices, ONNX on Android, Transformers.js in the browser
  • Docs & guides → openmed.life/docs

Why OpenMed

Private by design Models run locally, so clinical text can stay on hardware you control.
State of the art Clinical NER that set state of the art on 10 of 12 public biomedical NER benchmarks (arXiv 2508.01630).
Truly open Apache-2.0 SDK, and Apache-2.0 weights and recipes for 2,200+ models. Free for research and production.
Runs anywhere Python, iOS and macOS (MLX), Android (ONNX), the browser (Transformers.js), and servers.
Created by Maziyar Panahi and built in the open by 85 contributors.  ·  Guarded by our Persian-cat Avicenna — a local-first keeper of your data.  ·  GitHub · openmed.life