Human-learned lessons about machine learning in public health surveillance

Description: 

Presented December 13, 2018.

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, Epidemiologist and Surveillance Team Lead, National Center on Birth Defects and Developmental Disabilities, Centers for Disease Control and Prevention

Primary Topic Areas: 
Original Publication Year: 
2018
Event/Publication Date: 
December, 2018

December 21, 2018

Contact Us

National Syndromic
Surveillance Program

Email:nssp@cdc.gov

The National Syndromic Surveillance Program (NSSP) is a collaboration among states and public health jurisdictions that contribute data to the BioSense Platform, public health practitioners who use local syndromic surveillance systems, Center for Disease Control and Prevention programs, other federal agencies, partner organizations, hospitals, healthcare professionals, and academic institutions.

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