Prof. Dr.-Ing. Bert Arnrich

ClearRisk: Enhancing Predictive Modeling and Risk Communication in Digital Health Apps

Supervisors: Stefan Kalabakov, Jonas Chromik

Bachelor project students: Jannis Hajda, Tom Lawrence, Karl Schuetz, Theo Bardey, Gerome Quantmeyer, Uli Prantz, Julian Werne



Welcome to the world of ClearRisk, where we embark on a mission to improve patient outcomes and transform global healthcare. Each year, millions of lives are lost worldwide to cardiovascular diseases and related events such as heart attacks and strokes. In response to this critical issue, EU-funded projects like Pre-Care ML are dedicated to the early detection of high-risk patients, which would enable timely lifestyle changes that can significantly improve health outcomes.

However, these lifestyle changes are largely dependent on patients understanding their diagnosis and its severity, which is what this bachelor's project is all about. Specifically, in the ClearRisk project we are working on determining the most effective methods for conveying personalized risk scores for major cardiovascular events—such as heart attacks or strokes—to both patients and healthcare professionals, in an easily accessible manner.

To realize this vision, we have conceptualized a comprehensive system composed of the following:
1. Risk Assessment Service (RAS): A risk assessment service running on a server within a hospital, utilizing risk prediction models and patient data to provide personalized risk scores
2. Model-Based Risk Communication Strategy (RCS): An effective strategy to communicate risk information generated by the prediction models
3. User-Friendly Smartphone App: A smartphone app that integrates the best RCS and connects with the RAS, delivering personalized risk scores