Centaur - Annotate Medical Text Software
NLP, named entity recognition, and other AI methods generate insights from both structured and unstructured medical data stored as text. Our annotation platform can quickly tag thousands of text strings, conversations, paragraphs and more, organizing large volumes of text data for AI applications.
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Use cases
Unstructured clinical notes
Tag conditions and severity. Identify drugs prescribed. Tag symptoms after a drug protocol begins, and challenges patient experiences related to adherence.
Scientific literature
Classifying research citations and determining drug-target relationships in pharmacological literature.
Chatbot messages
Tag words and phrases that communicate intent, the severity of the patient condition, and act with appropriate urgency. Identify tone and sentiment to offer suggestions and improve experience.
Insurance claims
Identify interventions to contextualize and rationalize most recent intervention. Tag payouts and procedures from past claims. Identify prescribing behavior of HCPs.
Social media
Tag medical misinformation. Identify sentiment and symptoms shared when patients discuss a medication in a public forum.
Annotation types
- Classification
- Entity annotation
- Entity linking
- Sentiment annotation
- Semantic annotation
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