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DMMH 2013 : 2nd Workshop on Data Mining for Medicine and Healthcare


When May 4, 2013 - May 4, 2013
Where Austin, Texas
Submission Deadline Jan 7, 2013
Notification Due Jan 25, 2013
Final Version Due Feb 6, 2013
Categories    data mining   medical informatics   knowledge discovery   text mining

Call For Papers

Call for Papers

2nd Workshop on Data Mining for Medicine and Healthcare

To be held in conjunction with 13th SIAM International Conference on Data Mining (SDM 2013)

May 4, 2013
Austin, Texas, USA

Important dates
Paper Submission: January 7, 2013
Notification of Acceptance: January 25, 2013
Camera Ready Paper Due: February 6, 2013

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.

Workshop topics:
In addition to the more classical data mining approaches, this workshop aims to include two new topic fields – i.e. visual analytics and text mining in medicine and healthcare. By this extension, we aim to foster interactions among multiple communities that work at the intersections of data mining, 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
- 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.

Workshop Chairs:
David Gotz, IBM T.J. Watson Research Center
Nigam Shah, Stanford University
Gregor Stiglic, University of Maribor / Temple University
Fei Wang, IBM T.J. Watson Research Center

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