International Workshop on

Data Analytics for Evidence-based Healthcare

In Conjunction with the 19th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), Ho Chi Minh City, Viet Nam 19 - 22 May 2015


Healthcare systems around the world are under great pressure to incorporate evidence-based practices due to the large bodies of medical evidence available and the problems related to determining how the clinical evidence applies to specific cases. These problems are compounded by the multifaceted changes that our societies are experiencing: increase of aging population, funding problems, new and expensive treatments, translating evidence to practise and many more. In order to successfully transform the healthcare system into a more efficient system, some interdependent challenges need to be overcome, such as prevalence of tightly coupled applications and data; inadequate data and knowledge standards; insufficient analytics capabilities; unsatisfactory security and privacy methodologies; absence of a clinical decision-making foundation. Knowledge discovery and data mining techniques, especially data analytics, have been proven holding much promise for solving these problems. Providers can use health care data analytics to learn about patient populations, enhance preventive care and drive business decisions by accessing key data such as demographics and chronic conditions. Therefore, nowadays the healthcare industry requires a much more open, robust health information technology environment than ever existed, especially the techniques and methodologies in knowledge discovery and data mining.

Following on the success of DANTH’13(DANTH 2013) and DANTH’14(DANTH 2014), the DAEBH 2015 workshop focuses on how data analytics can improve information management in healthcare. The workshop will bring together researchers from different countries and regions to foster dissemination, increase the share of knowledge cross different domains, and strengthen the research on data analytic techniques and related applications to healthcare problems.


  1. -Healthcare Management Systems

  2. -Databases and Data Management

  3. -Data and Text Mining

  4. -Decision Making Support

  5. -Pattern Recognition and Machine Learning

  6. -Ontology and Standardization

  7. -Bioinformatics

  8. -Medical Image Analysis and Processing

  9. -Medical Signal Acquisition, Analysis and Processing

  10. -Health information visualisation

  11. -Medical Data Collection and Processing

  12. -Modelling of Physical and Conceptual Information

  13. -User Profiles and Personalised Healthcare

  14. -Social, Privacy, and Security Issues in Healthcare

  15. -Evaluation and use of Healthcare IT

  16. -Public health Surveillance


Information about DAEBH 2015 also available in KDnuggets, DBWorld and many other analytics and data mining resources.

Sponsored by the Centre for Health Informatics (CHI), Australian Institute of Health Innovation (AIHI) and Department of Computing, Macquarie University, Australia

DAEBH 2015 Flyer