DMMH 2015 - 4th Workshop on Data Mining for Medicine and Healthcare

4th Workshop on Data Mining for Medicine and Healthcare
To be held in conjunction with 15th SIAM International Conference on Data Mining (SDM 2015)
May 2, 2015
Vancouver, BC, Canada
http://www.dmmh.org/sdm15
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Important dates
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Paper Submission: January 12, 2015
Notification of Acceptance: January 30, 2015
Camera Ready Paper Due: February 9, 2015
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In virtually every country, the cost of healthcare is increasing more rapidly than the willingness and the ability to pay for it. At the same time, more and more data is being captured around healthcare processes in the form of Electronic Health Records (EHR), health insurance claims, medical imaging databases, disease registries, spontaneous reporting sites, and clinical trials. As a result, data mining has become critical to the healthcare world. On the one hand, EHR offers the data that gets data miners excited, however on the other hand, is accompanied with challenges such as 1) the unavailability of large sources of data to academic researchers, and 2) limited access to data-mining experts. Healthcare entities are reluctant to release their internal data to academic researchers and in most cases there is limited interaction between industry practitioners and academic researchers working on related problems.
The objectives of this workshop are:
1. Bring together researchers (from both academia and industry) as well as practitioners to present their latest problems and ideas.
2. Attract healthcare providers who have access to interesting sources of data and problems but lack the expertise in data mining to use the data effectively.
3. Enhance interactions between data mining, text mining and visual analytics communities working on problems from medicine and healthcare.
Topic areas for the workshop include (but are not limited to) the following:
- Statistical analysis and characterization of healthcare data
- Text mining - mining free text in electronic medical records
- Visual analysis and exploration of longitudinal clinical trial data
- Meaningful use of healthcare data for improved patient care and cost-reduction
- Data quality assessment and improvement: preprocessing, cleaning, missing data treatment etc.
- Pattern detection and hypothesis generation from observational data
- Visualization of prescriptions drugs and interactions
- Privacy and security issues in healthcare
- Information fusion and knowledge transfer in healthcare
- Evolutionary and longitudinal patient and disease models
- Medical fraud detection
- Hospital readmission analytics
- Help with ICD 9 to ICD 10 conversions
- Health Information exchanges
Paper submission and reviewing will be handled electronically. Authors should consult the workshop Web site for full details regarding paper preparation and submission guidelines at http://www.dmmh.org/sdm15.
Organizers:
Nitesh Chawla, University of Notre Dame
Gregor Stiglic, University of Maribor
Fei Wang, IBM T.J. Watson Research Center