OpenMed/OpenMed NER GenomeDetect ModernMed 395M
Entity recognition model for medical and genomic data
Pricing
See website
Flat rate
Adoption
→StableLicense
Open Source
Data freshness
—Overview
What is OpenMed/OpenMed NER GenomeDetect ModernMed 395M?
A token-classification model designed to identify named entities in medical texts, including genome-related information. This model is part of the OpenMed suite and has been trained on modern medical datasets.
Key differentiator
“This model stands out due to its specialization in recognizing entities within medical and genomic texts, offering high accuracy tailored specifically for these domains.”
Capability profile
Strength Radar
Honest assessment
Strengths & Weaknesses
↑ Strengths
Fit analysis
Who is it for?
✓ Best for
Researchers analyzing large volumes of medical and genomic text for entity recognition
Healthcare organizations looking to automate the extraction of key information from clinical notes
Developers building applications that require precise named entity recognition in medical contexts
✕ Not a fit for
Projects requiring real-time processing with strict latency requirements, as this model is designed for batch processing
Applications outside the healthcare domain where specialized medical and genomic knowledge is not required
Cost structure
Pricing
Free Tier
None
Starts at
See website
Model
Flat rate
Enterprise
None
Performance benchmarks
How Fast Is It?
Next step
Get Started with OpenMed/OpenMed NER GenomeDetect ModernMed 395M
Step-by-step setup guide with code examples and common gotchas.