Announcements

• Papers are due on Jan 14th 2012.

Workshop Description and Scope

Data Mining for Healthcare Management is an emerging field where researchers from both academia and industry have recognized the potential of its impact on improved healthcare by discovering patterns and trends of diagnosis, decisions and treatments in large amounts of complex data generated by healthcare transactions. Data mining has aided in several aspects of healthcare management including disease diagnosis, decision-making for treatments, medical fraud prevention and detection, fault detection of medical devices, healthcare quality improvement strategies and privacy. Data mining also helps to discover interesting business insights to help make business decisions that can influence cost efficiency and yet maintain a high quality of care.

Healthcare management has received great deal of attention in recent times and application of data mining techniques to this field is gaining increasing popularity. The large variety of such increasingly relevant issues strongly suggest the need for a workshop that provides a common platform for discussion of challenging problems and potential solutions in this emergence field of data mining for health care management. Data Mining for Healthcare Management workshop will provide a critical and essential forum for integrating various research challenges in this domain and promote collaboration among researchers from academia and industry to enhance the state-of-art and help define a clear path for future research in this emerging area. This workshop will facilitate collaboration among different disciplines including medicine, clinical studies, computer science and social scientists.

The workshop encourages the following topics (but is not limited to) related to application of data mining techniques to healthcare:

Care Delivery Healthcare resource management Patient relationship management Medical decision making Medical diagnosis Evidence based medicinal decisions Medical Insurance Fraud Detection Patient Flow Models in Hospitals Clinical data analysis Cloud-computing models and challenges

Privacy and security in healthcare. Health policy and economics Pattern recognition in medical images and data. Improving Quality of products and services Data collection and integration techniques Data cleaning and transformation Knowledge based medical recommendation models Information visualization of medical data. Medical device fault detection and prevention.

Important Dates

• Papers due: January 14, 2012
• Notifications: February 4, 2012
• Camera ready: February 11, 2012

Submission Instructions

Papers should be submitted via the EasyChair.

The paper should have at most 10 pages and use the SIAM style available at: http://www.siam.org/tex/books/soda2e.all.

More details on SIAM paper formatting can be found here. The paper must clearly present author information including name, affiliation and email.

Each paper will receive at least two reviews to determine acceptance.

Vipin Kumar, University of Minnesota
Tamara Winden, Allina Hospitals and Clinics
Bo Luo, University of Kansas.
Jayashree Kalpathy-Cramer, Oregon Health & Science University
Huzefa Rangwala, George Mason University
Ankur Teredesai, University of Washington
Fei Wang, IBM Almaden Research
Daniella Meeker, Rand Corporation
Alexander Senf, EBI, UK.
Kuo-Wei Hsu, National Chengchi University, Taiwan.

Organizing Chairs