Call for contributions
[Topics] [Submissions] [Templates]
Healthcare narrative (such as clinical notes, discharge letters, nurse handover notes, imaging reports, patients posts on social media or feedback comments, etc.) has been used as a key communication stream that contains the majority of actionable and contextualised data, but which – despite being increasingly available in a digital form – is not routinely analysed, and is rarely integrated with other healthcare data on a large-scale. The are many barriers and challenges in processing healthcare free text, including, for example, the variability and implicit nature of language expressions, and difficulties in sharing training and evaluation data. On the other hand, recent years have witnessed increasing needs and opportunities to process free text, with a number of success stories that have demonstrated the feasibility of using advanced Natural Language Processing to unlock evidence contained in free text to support clinical care, patient self-management, epidemiological research and audit.
The submission site is here.
Topics include but are not limited to:
- Language models for healthcare text analytics
- Information extraction: identification of clinical variables and their values in free-text
- Speech analytics for healthcare applications
- Medical ontologies and coding of healthcare 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
- Explainable models for healthcare NLP
- Text mining for veterinary medicine
- Real-time processing of healthcare free text
- Real-world application of text analytics
- Scalable and secure healthcare NLP infrastructures
- Implementation of healthcare text analytics in practice: public engagement and governance
- Sharing resources for healthcare text analytics (data and methods)
- Reproducibility in the healthcare text analytics
- Evaluation and assessment of text analytics methods
We invite various types of contributions (please use easychair for all submissions):
- Submissions will describe either methodological or application work that has not been previously presented in a conference. Papers may consist of between 4 and 8 pages, plus references. Accepted papers will be orally presented at the conference either as long presentations or as flash/lightning talks. As in previous years, there will be an open call to submit a journal length paper for further peer review and publication in Frontiers in Digital Health.
- Posters will describe ideas or ongoing work (e.g., projects), and will be offered space for presentation and discussion during the conference. Posters should be single-page submissions.
PhD and fellowship projects
Submissions by PhD students or early career researcher (ECR) fellows will be presented at the separate forum. These should present ongoing PhD research (in any stage) or a planned fellowship application. The forum will provide an opportunity to receive constructive feedback from the community, including a panel that will consist of the keynote speakers and experts in different areas. Contributions should consists of up to 4 pages and will be treated separately from the other submissions.
Panel discussions can be proposed to address the main challenges in processing healthcare free-text or to discuss the future of particular methodologies. Panels will be allocated one hour slots for discussions. Proposals for panels should consists of up to 2 pages.
Software demo sessions
- Demo sessions will provide a forum for demonstration of solutions and projects to the wider community. Up to 30-minute slots will be made available. Proposals for demos should consists of up to 2 pages.
- 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.