Second International Workshop on Social Media Analytics for Health intelligence
How artificial intelligence transforms healthcare

The fast expansion of social media in the last few years is making available an enormous and continuous stream of user-generated contents containing invaluable information that can be used to understand, in near real time, human life dynamics worldwide. These massive quantities of data could support in a wide range of medical and healthcare applications, including among others clinical trials and decision support, disease surveillance, personalized medicines and population health management. Besides, social media combines textual, temporal, geographical and network data, opening up unique opportunities to study the interplay between human mobility, social structure and disease transmission.
Artificial intelligence (AI) is changing the landscape of healthcare and modern personalized precision medicine. With the increasing availability of healthcare data and rapid progress of machine learning algorithms and analysis techniques AI is gradually enabling doctors for better diagnosis, disease surveillance, facilitating early detection, uncovering novel treatments, and creating an era of truly personalized medicine. Artificial intelligence in healthcare is going play a significant role in solving the issues like drug-interaction, false alarms, over-diagnosis, over-treatment. Moreover, AI with new technologies of IoT and Blockchain has tremendous scope for better medical treatment with data security.
The main areas of AI applications in healthcare are: providing personalized precision medicine, analysis and interpretation of radiology images, automated diagnosis, prescription preparation, clinical workflow monitoring, patient monitoring and care, discovery of new drugs, predicting the impact of gene edits, treatment protocol development, early diagnoses of diseases. The workshop provides a venue for the AI community to promote collaborations and present and exchanges ideas, practices and advances specific to social media use in the particularly challenging area of health applications. It serves as a unique forum to discuss novel approaches to AI and big data analytics and mining methods that are applicable to social media data and may prove invaluable for health monitoring, surveillance, disease spreading and outbreaks prediction. Although social media analytics research for health applications is still very much its infancy, it received a great attention along recent years. Several research studies appeared including, influenza surveillance, pharmacovigilance, user behavioral patterns, and tracking infectious disease spread.

Aims and Topics

The workshop solicits empirical, experimental, methodological, and theoretical research reporting original and unpublished results on social media analysis and mining on topics in the realm of healthcare and health informatics along with applications to real life situations. This can mean new models, new datasets, new algorithms, or new applications.

Topics of interest include, but are not limited to:

  • Personal health virtual assistant
  • Early disease diagnosis and treatment prediction
  • Clinical decision support in disease diagnosis and treatment
  • Analysis and interpretation of radiology images
  • Treatment Impact prediction
  • Methods for the automatic detection and extraction of health-related concept
  • 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
  • Community discovery and analysis
  • Large-scale graph algorithms for social network analysis
  • Spatio-temporal prediction of pandemics
  • Methods for capturing outbreaks of infectious diseases
  • Modeling the health status and well-being of individualsv
  • Models to predict the users’ moods from social posts
  • Real-time syndromic surveillance and early detection of emerging disease
  • Virus spread monitoring and modelization
  • Drug adversial reaction
  • 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
  • Medical imaging analysis and diagnosis assistance