Solutions
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.
Tag conditions and severity. Identify drugs prescribed. Tag symptoms after a drug protocol begins, and challenges patient experiences related to adherence.
Classifying research citations and determining drug-target relationships in pharmacological literature.
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.
Identify interventions to contextualize and rationalize most recent intervention. Tag payouts and procedures from past claims. Identify prescribing behavior of HCPs.
Tag medical misinformation. Identify sentiment and symptoms shared when patients discuss a medication in a public forum.
Testimonials
"Their user base combined with their application allowed us to easily and efficiently scale up our training data in a very controlled way that ensured it was high quality based on metrics we cared about in-house."
Co-Founder and CEO at scite.ai
"I get pitched on annotation tools all the time and Centaur is simply the best ... they offer you the accuracy and sophistication of medical experts at the price and speed of Mechanical Turk."
CEO at Factmata
1 email from the founders of Centaur Labs per month
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