AI is happening. The future is updating.OpenMed-ZeroShot-NER-Disease-Tiny-60M
**Specialized model for Disease Entity Recognition - Disease entities from the BC5CDR dataset** Specialized for **disease and condition recognition** from biomedical texts, covering clinical disorders and pathological states.Supports **patient phenotyping**, **disease indexing**, **literature triage**, and **clinical evidence aggregation**. OpenMed ZeroShot NER is an advanced, domain-adapted Named Entity Recognition (NER) model designed specifically for medical, biomedical, and clinical text mining. Leveraging state-of-the-art zero-shot learning, this model empowers researchers, clinicians, and data scientists to extract expert-level biomedical entities—such as diseases, chemicals, genes, species, and clinical findings—directly from unstructured text, without the need for task-specific retraining.
**Specialized model for Disease Entity Recognition - Disease entities from the BC5CDR dataset** Specialized for **disease and condition recognition** from biomedical texts, covering clinical disorders and pathological states.Supports **patient phenotyping**, **disease indexing**, **literature triage**, and **clinical evidence aggregation**. OpenMed ZeroShot NER is an advanced, domain-adapted Named Entity Recognition (NER) model designed specifically for medical, biomedical, and clinical text mining. Leveraging state-of-the-art zero-shot learning, this model empowers researchers, clinicians, and data scientists to extract expert-level biomedical entities—such as diseases, chemicals, genes, species, and clinical findings—directly from unstructured text, without the need for task-specific retraining.