KDD 2013 - Workshop on Data Mining for Healthcare (DMH)
August 11, 2013, Chicago, USA
Healthcare systems around the world are struggling to keep up with patient needs, and improve quality of care while reducing costs at the same time. At the same time automation in both healthcare services, data storage and record keeping are introducing new challenges. 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. Using this data in an effective way to improve quality of care and reduce costs requires innovation in data mining as well as academic, industry and government partnerships. On the system automation front, these challenges manifest themselves in the form of guarantees around healthcare system performances. Ascertaining reliability, data transmission quality and system availability have become increasingly more important as attempts are made to make remote healthcare systems as major enablers.
The goals of this workshop are to:
- bring together researchers (from both academia and industry) as well as practitioners from all four different groups in the healthcare system (patients, payers, providers, and pharmaceuticals) to talk about their different perspectives and to share their latest problems and ideas.
- attract healthcare professionals who have access to interesting sources of data and problems but not the expertise in data mining to solve them effectively. This group would otherwise not attend KDD and we believe through our personal experiences that it is essential for KDD research community to interact with them.
- bring in its purview the systems components of healthcare. These aspects have so far been covered only at networking or systems venues. However, these systems have significant dependencies and reliance on the type of data that they are intended to work with.
- bring in experts for a discussion on HIPAA and privacy, and how to enable data sharing for healthcare research in a HIPAA compliant environment.
Topic areas for the workshop include (but are not limited to) the following:
- Statistical analysis and characterization of healthcare 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
- Comparative effectiveness research
- Medical information retrieval
- Cloud-computing models and scalability
- Healthcare systems
- Privacy and security issues in healthcare
- Information visualization for healthcare data
- Information fusion and knowledge transfer in healthcare
- Evolutionary and longitudinal patient and disease models
- Mining knowledge from medical imaging data
- Medical fraud detection
- Case based reasoning
- Clinical decision support
- Informed consent
- Intelligent payment models
- Collaborative care delivery models
- Post-market surveillance of medical interventions
- Text mining - mining free text in electronic medical records
- Improving Clinical trial process
- Pay for performance models in healthcare
- Feasibility of Health Information Exchanges
- Health Information Exchanges
CFP also at: http://www.kdnuggets.com/cfp/