We invite two types of contributions (papers and special sessions) that address the variety of aspects involved in processing and using healthcare free text. Please see the Call for contributions for the topics. The submission templates are available here.

All submissions should be submitted in the PDF format via EasyChair. For selected conference papers, there will be the option to submit a journal length paper for further peer review and publication in Frontiers in Digital Health. In the past, post-conference special issues have appeared in Frontiers in Digital Health and Journal of Biomedical Semantics.




Full papers

  • Submissions should describe original, completed and unpublished work that focuses on either methodological or applicational aspects. Full papers may consist of up to 8 pages; accepted papers will be orally presented at the workshop. Selected full papers will be invited for a special issue in Frontiers in Digital Health.

Short papers

  • Submissions will describe original and unpublished work, potentially ongoing but with some findings; these will be presented as flash/lightning talks and will be also available as posters. Short papers may focus on either methodological or applicational aspects and may consist of up to 4 pages.


  • Posters will describe ideas or ongoing work (e.g. projects), and will be offered space for presentation during the conference. Posters should be single-page submissions.

PhD student papers

  • PhD student papers will be presented at the PhD forum, which will feature projects in healthcare text analytics. Contributions should consists of up to 4 pages and should present ongoing PhD research (in any stage). The forum will provide an opportunity for students to present their work to their peers and receive feedback from the community. These submissions will be treated separately from the other submissions.


Special sessions


Industry forum

  • Technology awareness, the “rebirth” of AI, and financial pressures are increasingly leading the health sector to engage with the text analytics industry for the provision of solutions to deliver data for research, administration and for regulatory requirements. The health sector presents the industry with a unique set of organisational, technical, social, and economic problems. The Industry Forum will be lead by a panel of experts from both industry and service procurement, and will explore these issues by presenting real world examples, and through in-depth discussion and debate with the audience.

Panel discussions

  • Panel discussions can be proposed to address the main challenges in processing healthcare free-text or to discuss the future of particular methodologies. A panel should focus on a specific challenge, application area or methodological development. It would typically feature 3-5 panelists giving a brief presentation or making a position statement, followed by discussion with an active role for the audience. Proposals for panels should consists of up to 2 pages and should clearly specify the motivation and aims, intended outcome (e.g. clarification of challenges), target audience and the structure of the session.

Software demo sessions

  • Demo sessions will provide a forum for demonstration of solutions and projects to the wider community. Proposals for demos should consists of up to 2 pages. Up to 30-minute slots will be made available. See more details.


  • Tutorials will provide opportunities for hands-on training on specific topics, methods or environments for the wider healthcare text analytics community, in any area of the interest. Proposals for tutorials should consists of up to 2 pages, indicating the motivation, main learning outcomes and intended audience. Tutorial slots will be discussed with the authors, considering half and full day events.


Submission templates

All contributions should be submitted in PDF format via EasyChair.

For all paper contributions, please use the HealTAC paper template (Word, Latex).

For special session proposals, please use the HealTAC session template (Word, LaTex).