News
- 08/03: The program schedule is up here. Looking forward to seeing everyone there!
- 08/02: Please find the proceedings here.
- 04/10: Accepting papers now. CFP posted and here is the workshop flyer.
- 04/01: Website is up!
Description
With escalating globalization, urbanization, and ecological pressures, the threat of devastating global pandemics becomes more pronounced. The impact of Zika, MERS, and Ebola outbreaks over the past decade has strongly illustrated our enormous vulnerability to emerging infectious diseases.
There is an urgent need to develop sound
theoretical principles and transformative computational approaches that will allow us to address
the escalating threat of a future pandemic. Data mining and Knowledge discovery have an
important role to play in this regard. Different aspects of infectious disease modeling, analysis
and control have traditionally been studied within the confines of individual disciplines, such as
mathematical epidemiology and public health, and data mining and machine learning. Coupled
with increasing data generation across multiple domains (like electronic medical records and
social media), there is a clear need for analyzing them to inform public health policies and
outcomes. Recent advances in disease surveillance and forecasting, and initiatives such as the
CDC Flu Challenge, have brought these disciplines closer––public health practitioners seek to use novel datasets and techniques whereas researchers from data mining and machine
learning develop novel tools for solving many fundamental problems in the public health policy
planning process. We believe the next stage of advances will result from closer collaborations
between these two communities, which is the main objective of epiDAMIK.
