The "MedRed" project is developing an innovative diagnostic tool that analyzes high-quality health data in order to recommend targeted preventive measures. The aim is to identify individual health risks at an early stage and prevent diseases before they develop. It uses probabilistic machine learning models that not only take existing biomarkers into account, but also identify new risk factors.

The multi-diagnostic tool combines modular data collection systems with personalized analysis models and creates reliable recommendations for users. This enables data-supported prevention, which plays a decisive role in reducing the risk of illness and minimizing health impairments such as absences from work or medical interventions.

The innovation of the project lies not only in the technological development, but also in the promotion of digital health solutions that raise awareness of preventive measures and reduce the burden on the healthcare system. Anonymized data analyses can also be used to sustainably improve working conditions, which is of great benefit to both companies and society.

The aim of the "MedRed" project is to develop a medically validated remote diagnostics tool that analyses individual health status and recommends personalized preventive measures for health promotion based on probabilistic machine learning methods. The aim of the diagnostic tool is to identify individual risk factors and provide targeted recommendations for health promotion that correspond to the findings of medical personnel in real time. The project is sponsored by the Central Innovation Program for SMEs (ZIM) of the Federal Ministry of Economics and Climate Protection (BMWK) with a total volume of around 423,000 euros.

Prevention is a central element of health promotion. Primary prevention in particular, i.e. measures that prevent illness before it occurs, plays a decisive role. However, the necessary incentives to motivate people to change their lifestyle in the long term are often lacking. As a result, preventive measures are not taken up sufficiently - a major challenge for the healthcare system. In addition, there is a lack of easily accessible, personalized services that take individual risk factors into account and provide targeted recommendations.

With innovative technologies such as the diagnostic tool developed in the "MedRed" project, it should be possible to detect diseases in advance and thus largely avoid secondary and tertiary prevention. The aim is to prevent diseases from developing in the first place instead of treating them or avoiding complications after a diagnosis. This not only reduces the health burden for those affected, but also contributes to a significant reduction in the burden on the healthcare system.

The coronavirus pandemic has shown how important digital healthcare solutions are. While there has been significantly less use of preventive check-ups, interest in home solutions has increased rapidly. However, existing services often only focus on individual aspects of health and do not offer a comprehensive analysis of an individual's state of health. This is where "MedRed" comes in: By identifying health risks at an early stage, targeted preventive measures can be introduced to promote long-term health and minimize the need for later interventions.