Demo sessions will provide researchers and practitioners a platform for demonstrating text analytics software systems and showcasing the benefits of text mining applications in healthcare. This will provide a great opportunity for conference attendees to witness and interact with state-of-the-art text mining systems. Demonstrated software is not required to be ready for commercial application. Research prototypes are welcome, but should clearly identify their research objective and the target user groups. Up to 30-min slots will be available.

Of particular interest are publicly available open-source or open-access systems. Areas of interest include all topics related to healthcare text analytics, including but not limited to:

  • Natural language processing of healthcare text
  • Information extraction: identification of clinical variables and their values in free-text
  • Machine-learning approaches to healthcare text analytics
  • Transfer learning for healthcare text analytics
  • Processing patient-generated data (e.g. social media, health forums, diaries)
  • Processing clinical literature and trial reports
  • Integration of structured and unstructured resources for health applications
  • Text analytics and learning health systems
  • Real-time processing of healthcare free text
  • Real-world application of text analytics
  • Text mining for veterinary medicine
  • Processing speech in healthcare applications


Preparing your demo proposals

The demonstration proposals should consists of up to 2 pages and include the following information:

  • Title
  • Authors (name, affiliation, email, address and phone)
  • Corresponding author
  • Abstract (max. 150 words)
  • Keywords
  • URL for the demo software (if available)
  • Paper reference if the work has been published (including this conference)
  • Equipment you will bring (e.g. laptop, projector)
  • Equipment you will need (e.g. table, poster board, power sockets)

Please use the HealTAC demo template (Word, LaTex) for all demo proposals.


Selection Criteria

  • Relevance to the HealTex community
  • Technical advances and challenges
  • Quality and soundness of the underlying technology
  • Potential for public interaction