openmed

name	openmed
description	Production-ready medical NLP toolkit (maziyarpanahi/openmed). Entity extraction, assertion detection, PII de-identification, batch processing, REST API, and multilingual support. Covers installation, all model families, configuration, and deployment.
tags	["medical-nlp","clinical-text","entity-extraction","deidentification","pii","icd10","healthcare","zorai","openmed"]

OpenMed

OpenMed transforms clinical text into structured insights. It bundles curated biomedical NER models, HIPAA-compliant de-identification, batch processing, a Dockerized REST API, and Apple Silicon acceleration — all behind a single analyze_text() call.

When to Use

Scenario	Start with
Extract diseases, drugs, anatomy from clinical notes	references/entity-extraction
Remove PHI/PII before sharing or storing data	references/pii-deidentification
Run NER on hundreds of clinical documents	references/batch-processing
Serve OpenMed behind a REST API	references/rest-service
Set up on Apple Silicon, Docker, or Swift	references/installation
Configure profiles, pick the right model	references/configuration
PII in French, German, Spanish, Portuguese, etc.	references/multilingual-pii
Privacy Filter (OpenAI / Nemotron) families	references/privacy-filter

Quick Start

git clone https://github.com/maziyarpanahi/openmed.git
cd openmed
uv pip install -e ".[hf]"

from openmed import analyze_text

result = analyze_text(
    "Patient started imatinib for chronic myeloid leukemia.",
    model_name="disease_detection_superclinical",
)
for entity in result.entities:
    print(f"{entity.label:<12} {entity.text:<35} {entity.confidence:.2f}")
# DISEASE      chronic myeloid leukemia          0.98
# DRUG         imatinib                           0.95

Model Registry (12+ Models)

Model	Entity Types
disease_detection_superclinical	DISEASE, CONDITION, DIAGNOSIS
pharma_detection_superclinical	DRUG, MEDICATION, TREATMENT
pii_detection_superclinical	NAME, DATE, SSN, PHONE, EMAIL, ADDRESS
anatomy_detection_electramed	ANATOMY, ORGAN, BODY_PART
gene_detection_genecorpus	GENE, PROTEIN

Browse the full catalog: openmed.life/docs/model-registry

Key Concepts

• analyze_text() — single-call inference with configurable model, aggregation, format, and confidence threshold
• BatchProcessor — multi-text and multi-file workflows with progress tracking
• extract_pii() / deidentify() — HIPAA-compliant PII detection and redaction
• Configuration Profiles — dev, prod, test, fast presets via YAML or env vars
• REST API — FastAPI endpoints: /health, /analyze, /pii/extract, /pii/deidentify

References

• OpenMed docs
• OpenMed arXiv paper
• OpenMed GitHub
• references/installation.md — cross-platform install, Docker, Swift
• references/entity-extraction.md — disease, drug, anatomy, gene models
• references/pii-deidentification.md — HIPAA compliance, smart merging, anonymization
• references/batch-processing.md — BatchProcessor API
• references/rest-service.md — FastAPI endpoints, Docker
• references/configuration.md — profiles, model registry, profiling
• references/multilingual-pii.md — 9-language PII support
• references/privacy-filter.md — OpenAI Privacy Filter, Nemotron, MLX