Digital Epidemiology: designing machine learning approaches to combine Internet-based data sources to monitor and forecast disease activity in multiple locations and spatial resolutions

Description: 

Presented May 24, 2018.

Mauricio Santillana, MS, PhD describes machine learning methodologies that leverage Internet-based information from search engines, twitter microblogs, crowd-sourced disease surveillance systems, electronic medical records, and historical synchronicities in disease activity across spatial regions, to successfully monitor and forecast disease outbreaks in multiple locations around the globe in near real-time.

Presenter

Mauricio Santillana, MS, PhD - Assistant Professor, Harvard Medical School; Faculty member, Boston Children's Hospital Computational Health Informatics Program; Associate, Harvard Institute for Applied Computational Science 

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

May 24, 2018

You voted 'down'.

Contact Us

INTERNATIONAL SOCIETY FOR
DISEASE SURVEILLANCE

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

This Knowledge Repository is made possible through the activities of the Centers for Disease Control and Prevention Cooperative Agreement/Grant #1 NU500E000098-01, National Surveillance Program Community of Practice (NSSP-CoP): Strengthening Health Surveillance Capabilities Nationwide, which is in the interest of public health.

Site created by Fusani Applications