Unsupervised Approaches for Phenotyping Using Electronic Health Record Data

Project Title Unsupervised Approaches for Phenotyping Using Electronic Health Record Data
Date
Wednesday, July 29, 2020
Description

Date and time

  • Wednesday, July 29, 2020, 12:00-1:00 PM ET

Description

  • An important goal of the Sentinel Innovation Center is to find ways to leverage machine learning approaches – including natural language processing and unsupervised learning – to identify health outcomes more efficiently. Computable phenotypes developed from electronic health record data could reduce both the cost and time needed to define and validate a gold standard. This webinar will focus on approaches for phenotyping using EHR data with a focus on annotation-free unsupervised classification methods such as PheNorm for phenotyping of medical conditions using electronic health record data. The discussion will consider the ways in which these approaches may be applicable to the Sentinel System.

Target Audience

  • Medical informaticists, medical product safety and real world evidence researchers and regulators
Host

Sentinel Innovation Center

Location

View a recording of the webinar here.

Presenters

Katherine Liao, MD, MPH

Related Assessments
Event Type
Webinar
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