Personal health is widely seen as the future of healthcare, with a focus on the 4Ps: Prediction, Prevention, Personalisation and Participatory healthcare.  This is distinct from pharmacogenomics or stratified therapies, but focuses instead on tracking our health – rather than illness – using wearable sensors and other home/wifi sensors to measure our physical state over time. This is a data-rich context in which Computational Intelligence (CI) can provide a wide range of tools for health-related knowledge extraction. Trends can then be identified which are used for a range of purposes from motivation for regular exercising to prevention and early screening for unexpected deterioration. Where individuals suffer from chronic conditions, this approach can help to target the right intervention at the right time.  This topic has links with health vaults, with avatars, as well as supporting care for the specific groups such as the elderly. This is a topic in which data integration is of key importance and different types of data can be brought in to provide context, ranging from demographics to social media.

• Solutions for heterogeneous data integration in personal health applications.
• Prototype applications of data analysis for personal health.
• ML and CI-based application in personal health.
• Intelligent analysis of wearable sensor data in health monitoring applications.  

• Intelligent analysis of health vaults data.
• Natural Language Processing for knowledge extraction from doctor’s prescriptions and/or patient’s feedback using mobile and tablet apps.