HealTAC-2018: Unlocking Evidence Contained in Healthcare Free-text
2nd Call for Contributions
We are delighted to invite you to contribute to the first UK healthcare text analytics conference. In this 2nd Call for Contributions, we are delighted to announce our keynote speakers (Prof Wendy Chapman, University of Utah and Prof Pierre Zweigenbaum, LIMSI-CNRS), a deadline extension for submission of papers and panel proposals (January 21st), and registration details.
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 demonstrate 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.
HealTAC 2018 will bring the academic, clinical, industrial and patient communities together to discuss the current state of the art in processing healthcare free text and share experience, results and challenges. We invite various types of contributions, including long and short papers, posters, PhD student papers, demos and panels, that address the variety of aspects involved in processing and using healthcare free text, including but not limited to
- Natural language processing of healthcare text
- Information extraction: identification of clinical variables and their values in free-text
- 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
- Real-time processing of healthcare free text
- Real-world application of text analytics
- Implementation of healthcare text analytics in practice: public engagement and trust
- Sharing resources for healthcare text analytics (data and methods)
- Evaluation and assessment of text analytics methods
- Text mining for veterinary medicine
- Processing speech in healthcare applications
The conference is sponsored by the EPSRC-funded UK healthcare text analytics network (Healtex). Submissions are welcome from all researchers interested in this area (including international). Details on how to submit a contribution can be found under Submissions section.
We are looking forward to welcoming you in Manchester in April!