🧬 OpenMed NER GenomicDetect ElectraMed 560M Specialized model for Gene Entity Recognition Gene related entities 📋 Model Overview 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. 🎯 Key Features High Precision : Optimized for biomedical entity recognition Domain Specific : Trained on curated GELLUS dataset Production Ready : Validated on clinical benchmarks Easy Integration : Compatible with Hugging Face Transformers ecosystem 🏷️ Supported Entity Types This model can identify and classify the following biomedical entities: B Cell line name I Cell line name 📊 Dataset Gellus corpus targets gene recognition and genetics entities for genomics and molecula…
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