Clinical ModernBERT combines advanced architecture with specialized medical knowledge, creating a powerful language model for healthcare applications.

• Trained on biomedical literature, clinical notes, and medical ontologies
• Features 8,192 token context length with Flash Attention for efficient processing
• Built on ModernBERT architecture with rotary positional embeddings (RoPE)
• Optimized specifically for clinical NLP tasks and biomedical applications

This research significantly advances clinical NLP by providing healthcare systems with deeper text understanding capabilities, potentially improving medical documentation, clinical decision support, and biomedical research.

Clinical ModernBERT: An efficient and long context encoder for biomedical text