MLHC 2017 - Machine Learning for Healthcare Conference 2017

MLHC -> Machine Learning for Healthcare Conference 2017
What: a two day meeting on data-driven healthcare
When: August 18-19, 2017
Where: Boston, MA
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 seven years, this meeting has drawn hundreds of 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 Deadline - April 24th 2017 at 6:00 PM (EDT)
Acceptance Notification - June 16th 2017
Program Chairs. Finale Doshi, PhD (Harvard University), James Fackler, MD (Johns Hopkins), David Kale (USC), Byron Wallace, PhD (Northeastern), Jenna Wiens, PhD (University of Michigan)