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Automated Drug Adverse Event Detection from Unstructured Text

Watch live on January 13th at 2pm EST

 

Adverse Drug Events (ADEs) are potentially very dangerous to patients and are amongst the top causes of morbidity and mortality. Monitoring & reporting of ADEs is required by pharma companies and healthcare providers. This session introduces new state-of-the-art deep learning models for automatically detecting if a free-text paragraph includes an ADE (document classification), as well as extracting the key terms of the event in structured form (named entity recognition). Using live Python notebooks and real examples from clinical and conversational text, we’ll show how to apply these models using the Spark NLP for Healthcare library.

Presented by Julio Bonis, a data scientist working on Spark NLP for Healthcare at John Snow Labs.