The University of Saskatchewan is hosting a bootcamp Nov. 12-17 on cross-leveraging big data, dynamic modeling and machine learning techniques for public health.
The event will provide participants hands-on experience in applying reliable and theoretically grounded techniques for cross-leveraging the strengths of Data Science and Systems Science to inform decision making in health. Participants will leave with a variety of take-home benefits, including practical skills in configuring, collecting and analyzing several sources of health big data (e.g., Social Feed Manager, Twitter, Ethica, Google Trends, and wearables), templates and code provided for analyses, and in visualizing such data with Apache Kibana and Ethica toolsets.
Types of big data featured for analysis and dynamic model linkage include–but are not limited to–patterns from dynamic contact networks (via smartphone-smartphone and smartphone-beacon collection), mobility, multiple types of online communicational behaviour, and accelerometry. Domains of health focus for case studies include opioid addiction, measles, tobacco and e-cigarette use, H1N1 Influenza (diverse examples), pertussis, foodborne illness control, sedentary behaviour, and suicide.