Deadline Extended until Friday 10/11!
NIPS 2013 Workshop on Machine Learning for Clinical Data Analysis and Healthcare
=== Call for Submissions ===
When: A one day (Dec. 10th) Workshop at NIPS
Where: Lake Tahoe, Nevada, USA
Website: Machine Learning for Clinical Data Analysis & Healthcare
Description:
Advances in medical information technology have resulted in enormous warehouses
of data that are at once overwhelming and sparse. A single patient visit may
result in thousands of measurements, and hospitals may see thousands of
patients each year. However, the average patient has relatively few visits to
any particular medical provider. The resulting data are a heterogeneous amalgam
of patient demographics, vital signs, diagnoses, records of treatment, medical
images, lab tests, and annotations made by nurses or doctors, each with its own
idiosyncrasies.
The objective of this workshop is to discuss how advanced machine learning
techniques can derive clinical and scientific impact from these messy,
incomplete, and partial data. We seek submissions on topics including
* Health monitoring systems
* Clinical data labeling
* Clustering and Phenotype discovery
* Clinical outcome prediction and tools for personalized medicine
* Efficient, scalable processing of clinical data
* Feature selection and dimensionality reduction in clinical data
* Timeseries analysis with medical applications
Submission Details:
Poster submissions should be extended abstracts no more than 4 pages in length
(in NIPS format, do not need to be anonymous). Extended abstracts should be
submitted by October 11 11:59 PM PDT via email to
[email protected]
Important Dates:
Submission - 11th October 2013 11:59 PM PDT
Notification - 23rd October 2013
Workshop - 10th December 2013
Organizers:
Jenna Wiens (MIT)
Finale Doshi-Velez (Harvard Medical School)
Madalina Fiterau (CMU)
Can Ye (CMU)
Le Lu (NIH)
Balaji Krishnapuram (Siemens Healthcare)
Shipeng Yu (Siemens Healthcare)
If you have questions about the workshop or the submission process please
contact the organizers [email protected]
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