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Biobert Chemical Ner
B
Biobert Chemical Ner
Developed by alvaroalon2
A biomedical named entity recognition model fine-tuned on BC5CDR chemical substances and BC4CHEMD datasets based on the BioBERT architecture
Downloads 5,175
Release Time : 3/2/2022
Model Overview
A named entity recognition model specifically designed for biomedical texts, capable of identifying biomedical entities such as chemical substances, supporting biomedical NER/normalization systems
Model Features
Biomedical Domain Optimization
Specially optimized for biomedical texts, excelling in chemical substance recognition tasks
Multi-dataset Joint Training
Jointly fine-tuned on two specialized chemical datasets: BC5CDR and BC4CHEMD
Open-source System Integration
Can be directly integrated into open-source BioNER/BioNEN systems
Model Capabilities
Chemical Substance Recognition
Biomedical Entity Recognition
Text Annotation
Use Cases
Biomedical Research
Literature Chemical Substance Extraction
Automatically identify chemical substance names from biomedical literature
Improves literature information extraction efficiency
Drug Development Assistance
Automatically identify relevant chemical substances during drug development
Accelerates R&D processes
Medical Information Processing
Electronic Medical Record Analysis
Extract drug and chemical substance information from electronic medical records
Assists clinical decision-making
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