Topics of interest include, but are not limited to:
• Crowdsourcing of network health data
• Methods for the automatic detection and extraction of health-related concept
• Data preprocessing and cleansing to deal with noise and missing data
• Streaming data mining
• Classifying and clustering of temporal health data in high dimensional spaces
• Application of deep learning methods to health data
• Novel architectures for scalable health data analysis and mining
• Statistics and probability in large-scale health social data analysis
• Community discovery and analysis
• Large-scale graph algorithms for social network analysis
• Social geography and spatial networks
• Mobility mining
• Spatio-temporal health data mining
• Spatio-temporal prediction of pandemics
• Methods for capturing outbreaks of infectious diseases
• Modeling the health status and well-being of individuals
• Models to predict the users’ moods from social posts
• Real-time syndromic surveillance and early detection of emerging disease
• Virus spread monitoring and modelization
• Detect health-related topics of discussion and events
• Drug abuse and alcoholism incidence monitoring
• Methodologies and measures to understand patterns and trends for general public health research