Defining corporate health classes
This project took place in winter term 2020, you CAN NOT apply to this project anymore!
Results of this project are explained in detail in the final documentation and presentation.
- Sponsored by: wellabe GmbH & Institute for Biological and Medical Imaging, Helmholtz Zentrum
- DI Incubator: Startup wellabe
- Project Lead: Dr. Ricardo Acevedo Cabra
- Scientific Lead: Dr. Dominik Jüstel, Jan Kukačka, Dr. Heiko Ott, Dr. Sebastian Dünnebeil,
- TUM Co-Mentor: PhD Candidate Konstantin Göbler
- Term: Winter semester 2020
The Munich-based corporate health start-up wellabe and the group for computation and analytics at the Helmholtz institute for biological and medical imaging (IBMI) join forces with you to analyse a unique dataset of health parameters acquired at the wellabe health checkups.
The wellabe health checkup is a rewarding experience and takes just 30 minutes. The detailed report helps to understand individual health improvement needs based on 60 measured biomarkers. From these biomarkers, wellabe builds Personalized Lifestyle Coaching around individual daily life, based on the most important biomarkers and the user’s preferences. The wellabe-app provides enlightening insights into the most important biomarkers and challenges the user where there is potential for improvement in an area that might affect health. The Body Age is a reference value that helps to track the user’s progress and keep his body young.
The corporate health dataset that will be analysed in this project and which consists of samples of biomarkers related to metabolism, cardiovascular system, body composition, respiratory system, and mobility, along with health status assessment by a medical doctor. The central goal of the project is to understand the structure of this datasets with respect to its information content regarding the health status of the users. The dataset offers opportunities for discovery of new, unknown relationships between health markers and medical conditions, as well as optimizing ways of diagnosing and predicting known conditions, possibly leading to reduction of health-related work disabilities.
Join our TUM-DI-LAB team with your data mining skills, exploring ways to understand a unique health dataset together with the teams of wellabe at the MTZ and the IBMI at TranslaTUM.