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.
• 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
Mohamed Ghalwash, Temple University
Andreas Holzinger, Medical University Graz
Robert Moskovitch, Columbia University
Mykola Pechenizkiy, Eindhoven University of Technology
Niels Peek, University of Manchester
Igor Pernek, Research Studios Austria
Chandan K. Reddy, Wayne State University
Stein Olav Skrøvseth, University Hospital of North Norway
Cristina Soguero Ruiz, Rey Juan Carlos University
Suzanne Tamang, Stanford University
Ping Zhang, IBM T.J. Watson Research
Jiayu Zhou, Michigan State University
Paper Submission: 27 Jan, 2016 (extended)
Notification of Acceptance: 5 Feb, 2016
Camera Ready Paper Due: 12 Feb, 2016
Workshop: May 7, 2016
All submissions must be made electronically at https://easychair.org/conferences/?conf=sdmdmmh2016.
Papers submitted to this workshop must not have been accepted or be under review by another conference with a published proceedings or by a journal. The work may be either theoretical or applied.
The workshop accepts short (4-6 pages) and long papers (up to 9 pages) with US Letter (8.5" x 11") paper size (single-spaced, 2 column, 10 point font, and at least 1" margin on each side). Papers must have an abstract with a maximum of 300 words and a keyword list with no more than 6 keywords.
We would like to encourage you to prepare your paper in LaTeX2e. Papers should be formatted using the SIAM SODA macro, which is available through the SIAM website. You can access it at http://www.siam.org/proceedings/macros.php. The filename is soda2e.all. Make sure you use the macros for SODA and Data Mining Proceedings; papers prepared using other proceedings macros will not be accepted.
For Microsoft Word users, please convert your document to the PDF format. Since there is no Microsoft Word Template, please visit http://www.siam.org/proceedings/ to view the format of previous papers.
All submissions should clearly present the author information including the names of the authors, the affiliations and the emails.
First Workshop on Data Mining for Medicine and Healthcare was organized at KDD 2011 conference in San Diego, CA. The workshop was implemented as a full-day workshop with 2 invited speakers, 6 full papers and 4 short papers.
Keynote lectures and the panel are available at http://videolectures.net/datamining2011_san_diego/.