bert-base-NER

Model · Token classification

OpenMed-NER-AnatomyDetect-ElectraMed-109M

OpenMed

Specialized model for Anatomical Entity Recognition - Anatomical structures and body parts This model is a state-of-the-art fine-tuned transformer engineered to deliver enterprise-grade accuracy for anatomical entity recognition - anatomical structures and body parts. This specialized model excels at identifying and extracting biomedical entities from clinical texts, research papers, and healthcare documents, enabling applications such as drug interaction detection, medication extraction from patient records, adverse event monitoring, literature mining for drug discovery, and biomedical knowledge graph construction with production-ready reliability for clinical and research applications.…

Model · Token classification

OpenMed-NER-SpeciesDetect-ElectraMed-109M

OpenMed

Specialized model for Species Entity Recognition - Species and organism names This model is a state-of-the-art fine-tuned transformer engineered to deliver enterprise-grade accuracy for species entity recognition - species and organism names. This specialized model excels at identifying and extracting biomedical entities from clinical texts, research papers, and healthcare documents, enabling applications such as drug interaction detection, medication extraction from patient records, adverse event monitoring, literature mining for drug discovery, and biomedical knowledge graph construction with production-ready reliability for clinical and research applications. This model can identify and…

Model · Token classification

OpenMed-NER-GenomicDetect-PubMed-109M

OpenMed

Specialized model for Gene Entity Recognition - Gene-related entities This model is a state-of-the-art fine-tuned transformer engineered to deliver enterprise-grade accuracy for gene entity recognition - gene-related entities. This specialized model excels at identifying and extracting biomedical entities from clinical texts, research papers, and healthcare documents, enabling applications such as drug interaction detection, medication extraction from patient records, adverse event monitoring, literature mining for drug discovery, and biomedical knowledge graph construction with production-ready reliability for clinical and research applications. This model can identify and classify the…

Model · Token classification

OpenMed-NER-DiseaseDetect-ElectraMed-109M

OpenMed

Specialized model for Disease Entity Recognition - Disease entities from the BC5CDR dataset This model is a state-of-the-art fine-tuned transformer engineered to deliver enterprise-grade accuracy for disease entity recognition - disease entities from the bc5cdr dataset. This specialized model excels at identifying and extracting biomedical entities from clinical texts, research papers, and healthcare documents, enabling applications such as drug interaction detection, medication extraction from patient records, adverse event monitoring, literature mining for drug discovery, and biomedical knowledge graph construction with production-ready reliability for clinical and research applications.…

Model · Token classification

OpenMed-NER-OrganismDetect-BioMed-109M

OpenMed

Specialized model for Species Entity Recognition - Species names from the Species-800 dataset This model is a state-of-the-art fine-tuned transformer engineered to deliver enterprise-grade accuracy for species entity recognition - species names from the species-800 dataset. This specialized model excels at identifying and extracting biomedical entities from clinical texts, research papers, and healthcare documents, enabling applications such as drug interaction detection, medication extraction from patient records, adverse event monitoring, literature mining for drug discovery, and biomedical knowledge graph construction with production-ready reliability for clinical and research…

Model · Token classification

OpenMed-NER-OrganismDetect-BioPatient-108M

OpenMed

Specialized model for Species Entity Recognition - Species names from the Species-800 dataset This model is a state-of-the-art fine-tuned transformer engineered to deliver enterprise-grade accuracy for species entity recognition - species names from the species-800 dataset. This specialized model excels at identifying and extracting biomedical entities from clinical texts, research papers, and healthcare documents, enabling applications such as drug interaction detection, medication extraction from patient records, adverse event monitoring, literature mining for drug discovery, and biomedical knowledge graph construction with production-ready reliability for clinical and research…