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Call for Submissions
MUCMD → Machine Learning in Healthcare 2016
What: a two day workshop on data-driven healthcare
When: August 19-20, 2016 (just after SIGKDD)
Where: Children’s Hospital Los Angeles, CA
Website: http://www.mucmd.org/
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Description. Researchers in machine learning --- including those working in 
statistical natural language processing, computer vision and related sub-fields 
--- when coupled with seasoned clinicians can play an important role in turning 
complex medical data (e.g., individual patient health records, genomic data, 
data from wearable health monitors, online reviews of physicians, medical 
imagery, etc.) into actionable knowledge that ultimately improves patient care. 
For the last six years, MUCMD has drawn about 100 clinical and machine learning 
researchers to frame problems clinicians need solved and discuss machine 
learning solutions; this year we are introducing a rigorous review process 
which will include both computer scientists and clinicians. Accepted papers 
will be (optionally) archived through the Journal of Machine Learning Research 
proceedings track.

We invite submissions that describe novel methods to address the challenges 
inherent to health-related data (e.g., sparsity, class imbalance, causality, 
temporal dynamics, multi-modal data). We also invite articles describing the 
application and evaluation of state-of-the-art machine learning approaches 
applied to health data in deployed systems. In particular, we seek high-quality 
submissions on the following topics:

*Predicting individual patient outcomes
*Mining, processing and making sense of clinical notes
*Patient risk stratification
*Parsing biomedical literature
*Bio-marker discovery
*Brain imaging technologies and related models
*Learning from sparse/missing/imbalanced data
*Time series analysis with medical applications
*Medical imaging
*Efficient, scalable processing of clinical data
*Clustering and phenotype discovery
*Methods for vitals monitoring
*Feature selection/dimensionality reduction
*Text classification and mining for biomedical literature
*Exploiting and generating ontologies
*ML systems that assist with evidence-based medicine

Proceedings and Review Process. Accepted submissions will be published through 
the proceedings track of the Journal of Machine Learning Research.  All papers 
will be rigorously peer-reviewed, and research that has been previously 
published elsewhere or is currently in submission may not be submitted.  
However, authors will have the option of only archiving the abstract to allow 
for future submissions to clinical journals, etc. 
Submission Details. Submissions should be no longer than 8 pages (excluding 
references). The review process is double blind. Please refer to the submission 
instructions on our website. 
Important Dates:
Paper Submission - May 15 2016 11:59 PM PDT
Acceptance Notification - June 15 2016

Senior Advsiory Committee. http://mucmd.org/index.html#program

Program Chairs. Finale Doshi, PhD (Harvard University), James Fackler, MD 
(Johns Hopkins), David Kale (USC), Byron Wallace, PhD (UT Austin), Jenna Wiens, 
PhD (University of Michigan)


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