Description This is a BERT-based model for classification of clinical documents sections. This model is trained on clinical document sections without the section header in the text, e.g., when splitting the document with ChunkSentenceSplitter annotator with parameter setInsertChunk=False. Predicted Entities Consultation and Referral, Habits, Complications and Risk Factors, Diagnostic and Laboratory Data, Discharge Information, History, Impression, Patient Information, Procedures, Other Live D...
