Displaying results 1 - 3 of 3
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A gentle introduction to using machine learning and NLP for health surveillance
Content Type: Webinar
Presented November 27, 2018. Unstructured data such as chief complaints and provider notes are an important component of effective Health surveillance. Applying machine learning (ML) and natural language processing (NLP) to unstructured data can… read more -
A Spatial Biosurveillance Synthetic Data Generator in R
Content Type: Abstract
To develop a spatially accurate biosurveillance synthetic data generator for the testing, evaluation, and comparison of new outbreak detection techniques. -
Exploring the Value of Learned Representations for Automated Syndromic Definitions
Content Type: Abstract
Comprehensive medical syndrome definitions are critical for outbreak investigation, disease trend monitoring, and public health surveillance. However, because current definitions are based on keyword string-matching, they may miss important… read more