Welcome
Welcome to the MaD Lab!
The researchers in the Machine Learning and Data Analytics (MaD) lab conduct theoretical and applied research for wearable computing systems and machine learning algorithms for engineering applications at the intersection of sports and health care. Our motivation is generating a positive impact on human wellbeing, be it through increasing performance, maintaining health, improving rehabilitation, or monitoring disease.
Student theses and projects
Our paper "Federated Electronic Health Records for the European Health Data Space" by Raab et al. was just published in The Lancet Digital Health. This collaborative effort between the MaD Lab and international experts in medicine, digital health and health policy, presents a novel approach to handl...
Bjoern Eskofier, Chair of Machine Learning and Data Analytics, has now been awarded by the Unipreneurs initiative under the patronage of the German Federal Ministry of Research and the German Federal Ministry of Economics.
The Unipreneurs initiative aims to identify and reward university professo...
Our new open-access article Artificial intelligence trend analysis on healthcare podcasts using topic modeling and sentiment analysis: a data-driven approach by Dumbach et al. was published in the Journal of Evolutionary Intelligence.
We describe a web mining approach to create a novel data set i...
We are happy to share the news that our latest systematic review on Mobile Health Apps in Breast Cancer Care by Flaucher et al. is now published in The Oncologist. With our systematic review, we investigated current methodology used to evaluate of mobile health interventions that are used in breast ...
Calling all researchers passionate about healthcare data!
Join us at our workshop, "Your Health, Your Data: Combining Interdisciplinary Views, Concepts, and Practices to Empower Patients in Their Engagement With Personal Health Data," held at the 'Mensch und Computer 2023' in September in beautif...
