*Call for Papers*

1st International Workshop on Deriving Value from Big Data in Healthcare in
conjunction with IEEE BigData 2015
http://knoesis.org/bigdata2value15/
October 29 — November 1, 2015, Santa Clara, CA, USA
——————————————————————————————————

*Overview*

Data related insights is expected to generate more than $300 billion a
year in the US health-care system. Healthcare data is multimodal spanning
EMR data, genomic, metabolomic, proteomic, environmental, behavioral, and
physiological data generating massive heterogeneous data stream. As an
example, Increased proliferation of low-cost sensors has resulted in
doctors gaining access to data from patient’s life as never before e.g.,
Pediatricians treating asthma may get data on environmental triggers using
sensors. Quantified Self movement exemplifies an increasing interest of
using commonly available low-cost sensors are increasingly being used to
monitor physical and physiological observations. This data has created
unprecedented opportunities in deriving valuable insights potentially
saving lives, saving billions, and improving quality and well-being of
people.

The Deriving Value from Big Data in Healthcare workshop aims to provide an
interdisciplinary forum for data scientists and clinical researchers to
exchange ideas and share information on their latest investigations on
deriving value from biomedical and healthcare data. We invite novel
techniques and algorithms for deriving value from this heterogeneous Big
Data in healthcare.


*Topics of Interest*


The topics of the workshop include but not limited to:

   - Clinical data, mainly the patient records from clinical institutions,
   such as electronic health records (EHR), medical imaging, trial data, etc.
   - Genotype data, the genetic makeups of the individuals, such as DNA and
   protein.
   - Social media data, which is the information the individuals posted on
   online social platforms such as Facebook, Twitter, PatientsLikeMe, etc
   - Environmental sensory data, which are the information sampled from the
   surrounding environment where the individuals are living in, such as air
   pollution and humidity information
   - Behavioral and sentiment data, which could be the data recorded by the
   wearable devices on patient’s activities
   - Mobile data, which are sampled from individuals’ mobile devices
   - Big data clinical modelling
   - Healthcare data integration and unification, which are platforms
   designed to integrate healthcare data resources
   - Cloud based healthcare data storage and reporting


*Important Dates*

   - Paper submission: September 3, 2015
   - Author notification: September 25, 2015
   - Camera ready of accepted papers: October 5, 2015
   - Workshop: October 29, 2015


*Submission*

High quality original submissions are solicited for oral and poster
presentation at the workshop. Papers should not exceed a maximum of 10
pages, and must follow the IEEE BigData format requirements of the main
conference (IEEE Computer Society Proceedings Manuscript Formatting
Guidelines).
All submissions will be peer-reviewed, and all accepted workshop papers
will be published in the proceedings by the IEEE Computer Society Press.

Submit you papers here
<https://wi-lab.com/cyberchair/2015/bigdata15/scripts/submit.php?subarea=S22&undisplay_detail=1&wh=/cyberchair/2015/bigdata15/scripts/ws_submit.php>.


*Advisors*

   - Ramesh Jain, University of California, Irvine
   - Amit Sheth, Kno.e.sis Center, Wright State University


*Organizers*

   - Jyotishman Pathak, Mayo Clinic
   - Maryam Panahiazar, Stanford University
   - Pramod Anantharam, Kno.e.sis Center, Wright State University
   - Satya Sahoo, Case Western Reserve University
   - Vahid Taslimitehrani, Kno.e.sis Center, Wright State University


*Program Committee (to be completed)*

   - Juan Banda, Stanford University
   - Tanvi Banerjee, Kno.e.sis Center, Wright State University
   - Ullas Nambiar, EMC
   - Parisa Rashidi, University of Florida
   - Mohammad Reza Siadat, Oakland University
   - Sreennivas Sukumar, Center for Intelligence Systems and Machine
   Learning
   - J.D. Whitlock, Mercy Health
   - Shipeng Yu, Linkedin

For general inquiries, please contact Vahid Taslimitehrani at <
[email protected]

-- 
Thanks and Best Regards,
Pramod Anantharam
Kno.e.sis Center, Wright State university.
http://knoesis.wright.edu/researchers/pramod/

--------------------------------
Brick walls are there for stopping those who do not want things badly enough
                                           -- Randy pausch
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