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Answering natural language questions

Watch live on September 16th at 2pm EST


The ability to directly answer medical questions asked in natural language either about a single entity (“what drugs has this patient been prescribed?”) or a set of entities (“list stage 4 lung cancer patients with no history of smoking”) has been a longstanding industry goal, given its broad applicability across many use cases.

This webinar presents a software solution, based on state-of-the-art deep learning and transfer learning research, for translating natural language questions to SQL statements. An actual case study will be a system which answers clinical questions by training domain-specific models and learning from reference data. This is a production-grade, trainable and scalable capability of Spark NLP Enterprise. Live notebooks will be shared to explain how you can use it in your own projects.

Presented by Prabod Rathnayaka - Graduate Research Assistant and PhD Student at La Trobe University