Call for Papers
The Symposium on Data Science for Healthcare (DaSH) is a premium forum that gathers leading researchers, practitioners, policy makers and thought leaders in related fields to discuss the latest innovative and visionary ideas, grand challenges, and future directions in leveraging big data for healthcare revolution. DaSH also provides valuable opportunities for scholars to disseminate their work, and fosters collaboration in a multi-disciplinary setting across different sectors for cross-fertilization.
After two successful events, the third DaSH symposium will be held October 19-20 at Ridgefield, CT, USA. The DaSH symposium is sponsored by the Leir Charitable Foundations, hosted by the Leir Retreat Center, and is supported by New Jersey Institute of Technology.
We invite extended abstracts on novel data science approaches to address healthcare issues in a broad spectrum, aiming for improving healthcare quality, reducing cost and improving accessibility. We encourage both contributions about system-building experiences, experimental studies, new applications, as well as visionary statements. Papers are solicited on a wide range of topics, including, but not limited to: information systems for healthcare; health data sharing, exchange and integration; health data quality; healthcare analytics and predictive modeling; natural language processing and text mining for healthcare; health service delivery and workflows; social media, mobile and Internet of Things for healthcare; health information visualization and system usability; privacy and security of health data; and health economics. We especially welcome papers that address data quality issues in healthcare this year.
All submissions will be reviewed by the program committee for novelty, soundness and significance.
(All deadlines are 11:59pm Eastern Time)
|July 31, 2017||Paper submission deadline|
|August 21, 2017||Author notification|
|August 31, 2017||Camera-ready deadline and author registration|
|October 19-20||DaSH symposium|
Papers should be electronically submitted in pdf format to https://easychair.org/conferences/?conf=dash2017.
Submissions are to be formatted according to the DaSH's camera-ready format, as embodied in the provided templates: either latex style file or word template file. These template files were adapted from the ACM templates. The submission must not exceed FOUR pages.
Authors who are willing to present a demonstration of their developed system, can mark their paper title as "Demo Proposal:" followed by the paper title in the first page of the paper.
Final versions of accepted submissions will be published in the electronic proceedings of the DaSH symposium. DaSH uses the Creative Commons license policy that allows authors to retain copyright while allowing DaSH to distribute their work broadly through modern media.
As a forum for leading researchers and practitioners to discuss the challenges and directions of Data Science for Healthcare, a senior author (e.g. a faculty member, a researcher or an experienced practitioner) of an accepted paper will be expected to attend the conference and present the paper. For accepted papers with several co-authors, the program committee reserves the right to select the co-author who should present the paper at the conference as a condition of acceptance. Participants are expected to attend the symposium at its entirety.
To ensure an intimate single-track experience with productive and in-depth discussions, the participation of the DaSH symposium is limited to authors of accepted papers based on the above requirements and attendees by invitation. Participants are expected to attend and be fully engaged during the entire event.
Thanks to the generous support of Leir Charitable Foundations and The Leir Retreat Center, the symposium registration, meals in the symposium, and one night hotel stay on October 19th will be covered and arranged by The Center.
- David G. Belanger - Howe School of Technology Management, Stevens Institute of Technology
- Yi Chen - Martin Tuchman School of Management, NJIT
- Soon Ae Chun - School of Business, The City University of New York
- Gordon Gao - Robert H. Smith School of Business, University of Maryland
- James Geller - Ying Wu College of Computing Sciences, NJIT
- Andrea L. Hartzler - Department of Biomedical Informatics and Medical Education, University of Washington
- Ketan Mane - Health Informatics, Kaiser Permanente
- Rao Praveen - Department of Computer Science & Electrical Engineering, University of Missouri-Kansas City
- Fei Wang - Weill Cornell Medical School, Cornell University
- Christopher C. Yang - College of Computing & Informatics, Drexel University