Call for papers

Following the exciting HealTAC 2018, the UK healthcare text analytics network (HealTex /hεlθεk/) is organising the second conference in the series next April in Cardiff, Wales.

Healthcare narratives recorded in documents such as discharge letters, imaging reports and patients' comments in surveys and on social media represent a communication stream that contains the majority of actionable and contextualised information. Despite them being increasingly available in a digital form, they are yet to be routinely analysed on a large scale. The conference aims to bring the academic, healthcare, industrial and patient communities together to explore the current state of the art and share best practice, key results and common challenges.

The first (formal) call for contributions will follow shortly, inviting long and short papers, posters, demos and special sessions. The event will also provide a forum for PhD students and industrial partners to present their work. The conference will be subsidised by HealTex – so please start preparing you contributions! Here are the key dates:

– Call for contributions: November 2nd, 2018
– Deadline for papers, posters, demos, special sessions: January 21th, 2019
– Notification of acceptance: February 18th, 2019
– Conference: April 24th and 25th, 2019

Please feel free to forward this information to your colleagues and collaborators.


  • Text mining: information extraction, term recognition, named entity recognition, sentiment analysis, text classification, information retrieval, language resources
  • Knowledge representation: development, application & standardisation of ontologies
  • Machine learning: feature engineering, case-based reasoning, naive Bayesian learning, support vector machines, genetic algorithms, genetic programming
  • Information management: data modelling, data mining, relational and XML databases, user interface development
  • Application areas: healthcare, life sciences, social sciences & social media


  • CMT207: Information modelling and database systems (postgraduate)
  • NOTE: All course resources are available through Learning Central.


  • Polona Štefanič (PhD, 2018-present): text mining, deep learning, acronyms
  • Daphné Chopard (PhD, 2018-present): text mining, deep learning, text normalisation
  • Anastazia Žunić (PhD, funded by the VC's International Scholarship, 2018-present): sentiment analysis, deep learning
  • Vignesh Muralidaran (PhD, funded by CorCenCC, 2017-present): natural language processing, corpus linguistics
  • David Rogers (RA, part time PhD, 2012-present): text mining, sentiment analysis, social media


  • David Owen (RA, 2016-2019): text mining, ontologies, health informatics
  • Dr Steven Neale (PDRA, 2016-2019): natural language processing, corpus linguistics, crowdsourcing
  • Daphné Chopard (MSc, funded by the Swiss-European Mobility programme, 2018): text mining, deep learning
  • Dr Lowri Williams (PhD, funded by EPSRC Doctoral Training Partnership, 2013-2017): text mining, sentiment analysis, language resources
  • Dr Bathilde Ambroise (PhD, 2012-2016): text mining, genomics, bioinformatics
  • Dr Bo Zhao (PhD, 2011-2015): text mining, ontologies, health informatics
  • Dr Christian Bannister (PhD, funded by MRC Doctoral Training Grant, 2011-2015): machine learning, health informatics, epidemiology
  • Dr Mark Greenwood (PhD, funded by CU President's Research Scholarship, 2010-2014): text mining, health informatics, social media