MLHC 2016 - Machine Learning for Healthcare (MLHC)

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
Patient risk stratification
Bio-marker discovery
Learning from sparse/missing/imbalanced data
Medical imaging
Clustering and phenotype discover
Feature selection/dimensionality reduction
Exploiting and generating ontologies
Text classification and mining for biomedical literature
Mining, processing and making sense of clinical notes
Parsing biomedical literature
Brain imaging technologies and related models
Time series analysis with medical applications
Efficient, scalable processing of clinical data
Methods for vitals monitoring
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 to MLHC. However, authors will have the option of only archiving the abstract to allow for future submissions to clinical journals, etc.
Important Dates:
Paper Submission: May 15, 2016
Conference: August 19-20, 2016.
Location: Los Angeles, CA