The goal of predictive medicine is to predict the probability of future diseases and to prevent or at least delay the onset of diseases through targeted prevention and intervention measures.

The most important factors influencing one’s own health are due to personal decisions. The right signals at the right time can bring the desired changes in behaviour. Ubiquitous digital technologies can make a significant contribution here, as users can be optimally reached. Health solutions as mobile apps can be a part of a learning and networked healthcare system.

AI and ML based algorithms can predict actionable interventions that serve long-term recovery or improve health maintenance. This enables healthcare professionals and patients themselves to proactively initiate lifestyle changes or increased medical monitoring. In order for algorithms to make reliable decisions, they require a large amount of historical data on which they can be trained. Data streams from electronic patient shares or data collected directly from patients (e.g. vital data collected through wearables) are increasingly used for predictive analysis.