Capability
Multi Label Phi Classification
4 artifacts provide this capability.
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1
stanford-deidentifier-baseModel46/100
via “multi-label-phi-classification”
token-classification model by undefined. 13,91,970 downloads.
Unique: Trained on radiology-specific PHI annotations, capturing entity type distributions and patterns unique to imaging reports (e.g., frequent institution names, date formats in imaging protocols). Uses PubMedBERT's biomedical vocabulary to better recognize medical entity types.
vs others: Provides entity-type granularity that generic NER models lack, enabling selective redaction strategies, while maintaining higher accuracy on clinical PHI types compared to general-purpose entity classifiers.