MOHRS 2017 - Workshop on Mining Online Health Reports

The Workshop on Mining Online Health Reports aims to bring together a cross-disciplinary community of researchers interested in automatically analysing consumer-generated data for health applications. Online health information is widely published by individuals in social media, chat rooms and discussion boards. At the same time search query logs and various forms of text messaging contain a vast amount of textual information that can be directly or indirectly linked to health conditions. This informal evidence about our individual health, attitudes and behaviours has the potential to be a valuable source for health applications ranging from real-time disease monitoring, to prioritising victim responses during disasters and detecting novel applications for drugs. Informal patient data on the Web is increasing, accessible, low cost, real-time and seems likely to cover a significant proportion of the population. Coupled with wearable body sensor data and the wealth of structured clinical data, it has the potential to offer insights leading to new lines of clinical investigation. However, in order to understand and integrate this data, researchers in academia and industry must grapple with theoretical, practical and ethical challenges that require immediate attention.
This one day workshop is structured around four main research questions:
- How can current sources of online health reports be characterised and what are the strengths and weaknesses of each?
- How are online health reports being processed using NLP/IR/ML technologies and/or integrated into traditional forms of health data such as biomedical databases and patient records?
- How is online health data being used in real-world case studies and field evaluations?
- What are the ethical/legal issues surrounding the exploitation of personal health reports?
We are inviting new and original work on a range of topics related to the automatic processing of online health reports, including, but not limited to:
- Semantics and NLP/IR/ML models for online health data
- Novel adaptations of methods to online health data
- Representation and integration of online health data
- Quantitative evaluation using online health data
- Open data sets related to online health
- Social network analysis / community identification for health applications
- Ethical/legal issues for online health data
- Reliability/trust issues with online health data
- Anonymisation and privacy preservation methods
- Online health data applications
- Theoretical underpinnings of online health techniques
- Case studies and qualitative evaluations
We warmly welcome: (a) Papers emphasizing novel algorithmic approaches to online health data; (b) Application-oriented papers that make innovative technical contributions to research; (c) Data papers sharing information about the construction and availability of novel data sets (please include a sample of the data and details about how the data set will be made available); (d) Case study papers describing the application of NLP/IR/ML to real world online health data processing with lessons learnt; (e) Papers that highlight any aspect of ethics for NLP processing of online health data, e.g. anonymization, evaluation issues around NLP applications, publication of data, use of NLP tools on sensitive data.
Important Dates
- Submission Deadline: November 11, 2016
- Notification to Authors: December 5, 2016
- Camera-ready PDFs due: January 27, 2017
- Workshop date: February 10, 2017
*** All deadlines are 11:59pm, anywhere in the world (Alofi time).
Submission Instructions
Submissions to the workshop will be subject to a double-blind peer review process, with each submission reviewed by at least two program committee members in addition to an organiser. Accepted papers will be given either an oral or poster presentation slot, and published online in the workshop proceedings.
Papers must be submitted in PDF format according to ACM guidelines and style files to fit within 8 pages (long papers) or 4 pages (short papers) including any diagrams, references and appendices. PDF files must have all non-standard fonts embedded. Submissions must be self-contained and in English. After uploading your submission, please check the copy stored on the site. Submissions that do not follow these guidelines, or do not view or print properly, may be rejected without review. The presentation format (oral or poster) will be decided by the program committee based on the nature, rather than the quality, of the work. There will be no distinction in the proceedings between papers that are presented orally or as posters.
PDF files submitted to the Workshop must be anonymised: The submitted document should not include author or affiliation information, and should not include citations or discussion of related work that would make the authorship obvious.
ACM style files (LaTeX and Word) are available from: https://www.acm.org/publications/proceedings-templ...
Submissions should be made using the EasyChair online submission system at https://easychair.org/conferences/?conf=mohrs2017
Organisers
- Nigel Collier (University of Cambridge)
- Nut Limsopatham (University of Cambridge)
- Ingemar J. Cox (University College London)
- Vasileios Lampos (University College London)
- Aron Culotta (Illinois Institute of Technology)
- Mike Conway (University of Utah)
Program Committee
- Eiji Aramaki (Nara Institute of Science and Technology)
- Matt-Mouley Bouamrane (University of Strathclyde)
- David Buckeridge (McGill University)
- Trevor Cohn (University of Melbourne)
- Karen Fort (Paris-Sorbonne University)
- Gareth Jones (Dublin City University)
- Taha Kass-Hout (US Food and Drug Administration)
- Gregoire Lurton (University of Washington)
- Iadh Ounis (University of Glasgow)
- Richard Pebody (Public Health England)
- Abeed Sarker (Arizona State University)
- Elad Yom-Tov (Microsoft Research)