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Supporting Mental Healthcare Delivery Using NLP

Today, mental healthcare services are available on-demand, 24×7, anywhere. At the same time, delivery of these services is severely supply constrained.

Machine Learning provides an opportunity to support, improve and scale the delivery of mental healthcare to a large number of people and address the supply-demand imbalance, while improving quality.

Our team at Headspace Health has been applying modern NLP techniques to augment the abilities of, and become a core component of our care providers’ workflows. We solve a breadth of problems spanning classification, retrieval, generation and unsupervised models.

In this talk, we will share an overview of some of the ways in which we are using NLP at various stages of our coaches’ interactions with members. These include identifying indicators of risk, recommending optimal level of care, increasing speed of repeating conversations, summarizing sessions into daily notes, and recommending self-care content from our content library.

Using NLP at Scale to Process Patient Charts for Identifying Patient Encounters

In this talk we will discuss how we will use NLP to process large patient charts and to identify patient encounters at...