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WEBINAR: Human-learned lessons about machine learning in public health surveillance
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For public health surveillance, is machine learning worth the effort? What methods are relevant? Do you need special hardware? This talk was motivated by these and other questions asked by ISDS members. It will focus on providing practical—and slightly opinionated—advice about how to determine whether machine learning could be a useful tool for your problem.

12/13/2018
When: Thursday, December 13, 2018
From 12 - 1:30 pm ET
Where: https://attendee.gotowebinar.com/register/7170697472461122563
United States
Contact: Catherine Tong

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Registration Link

https://attendee.gotowebinar.com/register/7170697472461122563

Presentation Description

For public health surveillance, is machine learning worth the effort? What methods are relevant? Do you need special hardware? This talk was motivated by these and other questions asked by ISDS members.  It will focus on providing practical—and slightly opinionated—advice about how to determine whether machine learning could be a useful tool for your problem.

Presenter

Matthew Maenner, PhD is currently an Epidemiologist and Surveillance Team Lead with the Developmental Disabilities Branch at CDC.  He came to CDC as an EIS officer in 2013, where he began developing a machine learning model to automate part of CDC’s autism surveillance system.  With colleagues, he received funding from CDC and the HHS Ventures Program to explore the applicability of this approach, examine new methods, and discover real-world issues that need to be considered if a machine learning model was put into practice. 

Webinar Recording

To be posted after the event.

Contact Us

INTERNATIONAL SOCIETY FOR
DISEASE SURVEILLANCE

288 Grove St, Box 203
Braintree, MA 02184
(617) 779 - 0880
Email: syndromic@syndromic.org

 

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